text:
Does the word "polymorphism" refer to the gene, the phenotype, or both?
In genetics, does the word "polymorphism" properly refer to genes, to phenotypes, or both? For example, if there are two alleles that lead to differences in the structure of the D2 neuroreceptor, would I talk about "a polymorphism in the gene for the D2 neuroreceptor" or "a polymorphism in the D2 neuroreceptor"? I've seen both uses in the literature, but it's not my primary field, so I don't have a feel for whether one is more widely accepted.
Bonus question: is there a preference regarding "polymorphism of," "polymorphism in," and "polymorphism on"?

The term "polymorphism" itself is more generally defined as "the quality or state of existing in or assuming different forms" (Merriam-Webster dictionary). So I guess semantically, it would be correct to say that there is polymorphism in a gene that can occur in different allelic variants, or polymorphism in phenotype because of variant traits (such as sexual dimorphism).
However, when biologists today speak of polymorphisms, often they refer to variations at the level of individual nucleotides (single nucleotide polymorphisms or SNPs; some people use the terms polymorphism and SNP interchangeably). These SNPs have become popular for genotyping and for correlation with a variety of diseases or other observable phenotypes.
And regarding the bonus question, I think "polymorphism in" is the most correct usage--it's definitely the most widely used. For example, you could say "there is a polymorphism in nucleotide 257 of..." or simply "there is polymorphism in nucleotide 257 of..." or even "nucleotide 257 of ... exhibits polymorphism".

A difference in phenotypes might result from polymorphisms, but one doesn't refer to those differences as polymorphisms.


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Two subunits connected by only one disulfide bridge: quaternary structure?
I've always simply assumed quaternary structure to be characterized by non-covalent interactions such as hydrogen bonding, van der Waals interactions and whatnot. However, if two distinct polypeptides were only connected by one covalent disulfide bridge, would this be considered as quaternary structure, assuming that non-covalent interactions between the subunits are either negligible or even repulsive?
In other words, can a disulfide bridge, on its own, convey quaternary structure?
On a side note, are there any notable examples of this type of interaction?

I don't know of any examples of this but I would say no doubt, that's quarternary structure. Quarternary isn't so much defined by the kind of interaction but much more the fact that it's between different polypeptides; all lower-level structures are within one polypeptide. (Wikipedia agrees.)

I've always just gone with the name hetereodimer but there isn't any technical reason why it isn't a quaternary structure. As for an example, I work with antibody fragments or FAbs and cys-diabodies which are exactly that, two distinct polypeptides that are connected by a disulfide bond linkage.
These do have a significant amount of non-covalent interactions. For something with less, maybe ricin?

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How fast do different organs turn over cells?
It is said that the human body turns over all cells or molecules in 7 year cycles. This is not quite correct, because there are different organs changing at different speeds. My interest is what is the scale of change and especially, is it possible to measure and how fast do:
1) cells change
2) molecules change
3) atoms change
High, medium and max rate organ examples would be appreciated.

1) cell growth
You should look into chemotherapy and cancer medicine in general.  Because chemo is mostly effective because it kills fast dividing cells, this has been worked out reasonably well.  the 7-10 year number is not really correct, some cells are replaced a lot more slowly.
This is why hair often falls out in cancer treatment, because the follicle cells are growing quickly.  Neurons divide very slowly - if at all - and often are never replaced.  Fat cells are in between - probably replaced in the 7-10 year range.  Heart cells are replaced albeit quite slowly - less than 1% per year, which implies that many cells are with you your entire lifetime.
2) atoms/molecules change
The cell itself is in a continuous state of flux, but different parts of the cell, like cells in the body, change at different rates. Some proteins which make up the cell matrix or the DNA in the nucleus are replaced very rarely (through repair or rearrangement of the chromosome for instance) and most of the chromosome DNA is with the cell for the entire life of the cell.
Most proteins are labelled for degradation and are recycled after a few hours of function.  Metabolic compounds such as sugars or salt might drift in and out of the cell continuously, maybe turning over in an hour or so. Fats can be incorporated into the cell and last for years I think.

Is it possible to make/get a chart of different main organs and their turn over time?

For (1) it should be - oncologists probably have a lot of this information in their heads, and probably you can walk through a few textbooks and get some basic information.  there are always new kinds of cells to be discovered it seems though.

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What are samples of "Outlaw Genes"
I read this in a paper

Keller and Ross describe their greenbeard gene as an ‘outlaw’.
  Admittedly, the comment is only made in passing, but are they correct?
  In this context an outlaw is usually defined as a gene whose action
  favours itself, but opposes the reproductive interests of the
  individual organism. Where there are outlaws, natural selection at
  different loci is pulling the organism in different directions.
  Theoretically speaking, green-beard genes...

Yes: http://www.sciencedirect.com/science/article/pii/S0140175083901562
Basically loving your children is outlaw because it makes you sacrifice resources for your children. However, if your interest is defined as maximizing the number of children, then it's just your stuff working properly. Outlaw genes will be something that makes you die for a cause or stuff like that I suppose.

It's a gene that motivate the host to kill individual that don't have that genes.

Okay, a good edit, but what is your actual question now?

Are there genes that survive well in the genepool in ways that hurt their hosts' gene pool survival. That is the definition of outlaw genes.

The t locus, which is described in detail in this book by Robert Trivers, is the classic 'outlaw' or 'selfish' gene.
If a heterozygous (single) t allele is present in the paternal mouse, the t locus is evident in sperm 95% of the time.  Talk about "Breakin' the Law"!  As a locus whose main phenotype seems to be for mitotic cheating, t seems to convey little or no benefit to the other genes by way of helping the host survive.  t/t homozygotes are sterile.  Nice summary here.


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How does Artificial Selection work?
As far as I know for evolution to work mutations  are necessary. Mutations are the raw material on which natural selection works.
But mutations are always completely random and human beings have no control over it.Then my question is how artificial selection works? Would it have been possible to domesticate dogs from wolves, if there would have been no mutations in wolves to begin with?

artificial selection != evolution.

I would even say evolution > selection

Both natural selection and artificial selection require genetic variation in the underlying population to work.  The exact source of this genetic variation is not particularly important theoretically.  In reality this genetic variation originally comes from mutations of various sorts (not just point mutations, but also duplications, recombinations, etc.).  If you had no genetic variation then artificial selection would not be effective.
You might be interested in Stephen Jay Gould's essay "A Dog's Life in Galton's Polyhedron" (found in the collection "Eight Little Piggies"), where he explains that domestic dogs have very little variation in skull length (relative to body size), but large variation in skull width.  It seems that it is very difficult to artificially select for dogs whose skull and body don't have the correct ratio, even though you can wildly change the sizes of dogs, the width of their skulls, the length of their legs, etc.

You seem to have a few different concepts in there...

But mutations are always completely random and human beings have no control over it.

Aside from the fact that mutations are not completely random (not always, at least), it is not true that humans have no control over them. Imagine you grow plants, and you start to cross those plants that have a larger stalk, allowing them to be more resistent to wind: you are effectively selecting a certain mutation. Surely, you cannot choose which specific sequence you want to mutate, but still you are enriching your population of plants with a specific mutation.
Nowadays of course you can specifically mutate the genome in the lab, but that is a different matter.

Would it have been possible to domesticate dogs from wolves, if there would have been no mutations in wolves to begin with?

Note that artificial selection has been used to generate the different breeds of dogs, by breeding animals with specific characters.
However, domestication is a different matter. Wolves and dogs are the same species (Canis lupus) and domestication is not strictly dependent on selective breeding. You can domesticate an adult animal without inducing mutations in its DNA. Probably epigenetics plays an important role there, and epigenetic patterns could possibly be transmitted to the offspring.
Of course, then you will use selective breeding to expand the domesticated population, and to select those traits you are interersted into. With artificial selection you are just selecting the mutations you want, the way you generate them is irrelevant to the matter: for instance you can irradiate plants to enhance mutation rate, and consequently the appearance of new favorable traits.

But imagine a hypothetical situation, where there is no mutation at all. Then can artificial selection work?

@user774025: well, no, but natural selection would not work either then...

even if there is no mutation, as long as there is variation within the population, selection (artificial or natural) will work

@Richard Smith: and how would you have variation without mutation?

Sex, recombination, viral introgression, etc. I interpreted the 'hypothetical situation' as there being no mutation happening now. In a hypothetical system where there was never any mutation, there could only be variation if you started with variation.

@Richard Smith: well, technically speaking those are examples of mutations, as you are changing the genome. Replication without some mutation would be some sort cloning. Anyway, it is not only an hypothetical situation, but an absurd one :) Point is: whether you are selecting mutations by natural selection, by looking at the phenotype or by inducing them in a lab, more or less specifically, the output is always the same.

@nico good point, I was thinking of a very narrow definition of mutation.

Accumulated mutations over generations will make up the genetic variation present in a population for a species. For example, wolves naturally had a certain amount of genetic variation, or diversity, before humans started domesticating wolves. They still do, but to a lesser extend now since their populations have decreased.
Artificial selection is different from natural selection in that is forced artificially by us, humans, upon a species, like wolves, to change the traits to our liking. The first few traits that were artificially selected from wolves were probably related to their behavior: being more submissive and less erratic in their behavior. Then different people started crossing different breeds with interesting traits to try and combine the desired traits into new breeds.
One of the consequences of such dramatic breeding efforts is a decrease in haplotype diversity in dog breeds and higher incidence of undesired diseases. That is, during the crossing of breeds, part of the natural variability in the original populations was lost, and the resulting breeds only had one identical haplotype (in both copies) for many areas of the genome where there used to be two distinct ones, and if that haplotype was bearing an allele for a recessive disease, it showed up in homozygosis. This is the reason why for many important species of plants and animals, there are efforts to try and keep the original wild populations alive, in case we need to draw from the genetic diversity when the domesticated breeds need more.


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What are Haplogroups?
What exactly does the term Haplogroup or Haplotype means?
How is it claimed that people belonging to the same haplogroups have common ancestors?

I understand haplogroup as the group of people that share the same given haplotype for a region of the genome.

what is haplotype?

I understand haplogroup as the group of people that share the same given haplotype for a region of the genome.
A haplotype is the readout of the DNA sequence for a part of the genome in one of the two copies that diploid organisms have. If you start reading the DNA sequence for a given point in the genome from one of your copies and someone else's copies, it will coincide up until a point where there is a change. It is more probable to have longer identical haplotypes if the two people that are compared are related. The closest the relation, the longer their haplotypes will be identical. What breaks haplotype identity are recombination events that happen in the germinal line in the previous generation, and mutations that happen both in the germinal line and the soma (the rest of your body) along time.

haplogroup can be an assumed relationship as well - where ethnic groupings may be assumed to have common regions of variants... (e.g. caucasian, east asian, ashkenazi jews, yoruban africans are commonly referenced haplo groups).


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Why did high A+T content create problems for the Plasmodium falciparum genome project?
The main paper for the Plasmodium palciparum genome project (Gardner et al., 2002) repeatedly mentioned that the unusually high A+T content (~80%) of the genome caused problems. For example they imply that it prevented them using a clone-by-clone approach:

Also, high-quality large insert libraries of (A + T)-rich P. falciparum DNA have never been constructed in Escherichia coli, which ruled out a clone-by-clone sequencing strategy.

And that it made gene annotation difficult:

The origin of many candidate organelle-derived genes could not be conclusively determined, in part due to the problems inherent in analysing genes of very high (A + T) content.

Question:
What is the biological significance of high A+T content, and why would it cause problems in genome sequencing?
Ref:
Gardner, M.J., Hall, N., Fung, E., White, O., Berriman, M., Hyman, R.W., Carlton, J.M., Pain, A., Nelson, K.E., Bowman, S., Paulsen, I.T., James, K., Eisen, J.A., Rutherford, K., et al. (2002) Genome sequence of the human malaria parasite Plasmodium falciparum. Nature. 419 (6906), 498–511.

I am not an expert in molecular biology so I will leave this as a comment. I think the problem is the same as for G/C rich regions: if you mostly/only have A and T you have much less possible combinations of nucleotides and you will have many more overlapping sequences in the genome, which will hinder sequencing because it will be difficult to overlap the clones.

Good point nico, so by reducing the complexity you increase the chance of having non-unique ends.

The sequencing technologies that were developed in the last 20 years have a range of optimal use at an average A+T/G+C rate. Both highly AT-rich and GC-rich regions are complicated to process by the different sequencing technologies. Each technology has different ranges of usage, but to name one, Illumina technology prefers sequences in the middle range. If you try to sequence an AT-rich genome with the Illumina standard protocol, you will sequence an incomplete genome, the fragments of which are not a perfect reflection of the original complete genome. Other technologies claim to be completely unbiased to nucleotide content. Pacific Biosciences is one of them, and people seem to agree on that claim, after having analyzed the data that is produced by their machines. Oxford Nanopore Technologies claims that they have almost no biases, but as of today (2012-06-13), there is no confirmation of that by external analyses.
Beyond sequencing problems, the software used to assemble and annotate the sequences may also be prone to errors in AT-rich and GC-rich regions. But many of those problems stem from the incompleteness of the sequencing.

I can't comment on how A+T richness complicates the sequencing process itself, but I can comment on complications that arise when annotating the sequence. Ab initio gene predictors are often based on hidden Markov models that are very sensitive to base composition in the genome (di-nucleotides, tri-nucleotides, etc). These gene finders typically perform very poorly if they are run on a genome that has a much different base composition than the one on which it was trained. This could explain some of the difficulty they has with analyzing genes in the genome.

Often sequencing involves a step of amplification of genomic material. The standard way to perform this is with PCR, but PCR is biased and does not amplify very AT-rich regions well. With multiple rounds of PCR, even low-abundance regions that are not as AT-rich might come to dominate the sample and hide the AT-rich sequences.
This is not only a problem for de novo sequencing, but for many sequencing-based techniques (RNA-seq, ChIP-seq, your-favorite-seq...). Alternative methods have been employed in plasmodium, but they are not as standard (yet?).
See, for example, H2A.Z Demarcates Intergenic Regions of the Plasmodium falciparum Epigenome That Are Dynamically Marked by H3K9ac and H3K4me3 at http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1001223

In the past, before massively parallel sequencing, they made a library of cloned sequences and transformed these into E. coli. High AT sequences are difficult to maintain in E. coli (perhaps due to similarity to promoters?).

A lot has already been said in previous answers so I am just gonna add briefly two potential issues with strong AT/CG bias:
1) Potential for polymerase slippage due to homopolymers: this introduces errors in general because you may have unwanted indels in the reads as well as purely incorrect bases being incorporated. This is a problem that can happen even with PCR (although there's a lot of choices now if u want to spend). So in general higher error rates and higher read failure.
2) Difficulty of the machine to separate the signals of individual nucleotides for SANGER (it gets all blurred) or calibration errors with next gen sequencing. So higher read failure (bad quality).
3) Assuming everything is now fine, still lower complexity regions can be VERY hard to map, let alone assemble a complete genome from scratch.
Hope this helps!


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Introductory literature for synthetic / systems biology
I am a computer engineer (MSc in Computer Engineering) who's looking to switch into the field of synthetic / systems biology. I have a comprehensive layman's understanding of evolution, genetics, transcription, etc, but my academic studies have been in the areas informatics, computer science, computer engineering and mathematics.
Does anyone have a good recommendation for standard literature in the field, to get me up to speed?

An Introduction to Systems Biology By Uri Alon.

Systems Biology
Wingreen & Botstein who run the graduate systems biology course at Princeton wrote a paper about how to teach the subject (Wingreen & Botstein, 2006). In the paper they highlight the key concepts they think are crucial to understanding modern systems biology, and they teach the course through discussion of seminal papers in the field.
Here's the reference...
Wingreen, N. & Botstein, D. (2006) Back to the future: education for systems-level biologists. Nature Reviews Molecular Cell Biology. 7 (11), 829–832.
The paper is unfortunately not open access, so for those who can't access the paper  edit: @uvesten found a free PDF copy! I have listed their choices below, along with the key concept they think each provides...
Robustness (i.e. retaining function despite fluctuations)
Barkai, N. & Leibler, S. (1997) Robustness in simple biochemical networks. Nature. 387913–917.
Evolutionary perspective
Eisen, J.A. (1998) A phylogenomic study of the MutS family of proteins. Nucleic Acids Res. 264291–4300.
Microarray analysis (and more generally, the importance of data visualisation)
Eisen, M.B., Spellman, P.T., Brown, P.O. & Botstein, D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA. 9514863–14868.
Individuality of elements in a system:
Elowitz, M.B., Levine, A.J., Siggia, E.D. & Swain, P.S. (2002) Stochastic gene expression in a single cell. Science. 2971183–1186.
Maximum likelihood
Felsenstein, J. (1981) Evolutionary trees from DNA sequences: a maximum likelihood approach. J. Mol. Evol. 17368–376.
Ultrasensitvity
Goldbeter, A. & Koshland, D.E. (1981) An amplified sensitivity arising from covalent modification in biological systems. Proc. Natl Acad. Sci. USA. 786840–6844.
Biophysical modelling
Hodgkin, A.L. (1958) Croonian Lecture, ionic movements and electrical activity in giant nerve fibres. Proc. R. Soc. Lond. B. Biol. Sci. 1481–37.
Specificity
Hopfield, J.J. (1974) Kinetic proofreading: a new mechanism for reducing errors in biosynthetic processes requiring high specificity. Proc. Natl Acad. Sci. USA. 714135–4139.
Random processes and distributions:
Luria, S.E. & Delbruck, M. (1943) Mutations of bacteria from virus sensitivity to virus resistance. Genetics. 28491–511.
Stable switching between states:
Novick, A. & Wiener, M. (1957) Enzyme Induction as an all-or-none phenomenon. Proc. Natl Acad. Sci. USA. 43553–566.
Sequence similarity
Smith, T.F. & Waterman, M.S. (1981) Identification of common molecular subsequences. J. Mol. Biol. 147195–197.

Synthetic Biology
A good place to start in this subject is the Synthetic Biology network:

Syntheticbiology.org
iGEM.org
BioBricks.org

With some google-scholar-fu I found this link: http://www.princeton.edu/genomics/botstein/publications/2006_Wingreen_Back.pdf Is that the correct article?

That's the one, good job finding a pdf :)

Downvoters should have to leave comments. How can I improve the answer? Simply downvoting without commenting is not a positive contribution.

And http://DIYBio.org!

I have a similar background (CS switching to systems biology) and I learned a great deal by reading "Systems Biology: A Textbook" by Edda Klipp et al [1]. It's a very good overview of different sub-areas and it's written in a way that's friendlier to a technical mind than most other bio-related books (i. e. concise, to the point, not shy with formulas). The section about experimental techniques is a real treasure, at least for me getting used to the ways in which we can look into cells was the biggest challenge.
Another text you might look into is "An Introduction to Systems Biology" by Uri Alon, but it's very dynamic modelling-oriented and will give you less of an overview.
[1] http://www.amazon.co.uk/Systems-Biology-Textbook-Edda-Klipp/dp/3527318747/ref=sr_1_1?ie=UTF8&qid=1339413559&sr=8-1
[2] http://www.amazon.com/Introduction-Systems-Biology-Mathematical-Computational/dp/1584886420

There is a recent published book, from Garland Science for systems biology
http://www.garlandscience.com/product/isbn/9780815344674
and a clasic textbook: Physical Biology of the Cell
http://www.garlandscience.com/product/isbn/9780815341635

I've been working to prepare a synthetic biology curriculum for non-biologist and have found a great resource in Prof. Scott Mohr's (BU, Chemistry) "Primer for Synthetic Biology" available here:
http://openwetware.org/images/3/3d/SB_Primer_100707.pdf

Many people switch to systems biology from a math/physics/computer science background and may need a cell biology textbook to update them on general biology knowledge.
*For molecular biology knowledge:*A comprehensive and reliable biology text on the graduate level is "Molecular Biology of the Cell" by Alberts:
http://www.amazon.com/Molecular-Biology-Cell-Bruce-Alberts/dp/0815341059/ref=sr_1_1?ie=UTF8&qid=1361575051&sr=8-1&keywords=molecular+biology+of+the+cell
*For biochemistry knowledge, especially related to metabolic pathways:*A more Biochemistry focused textbook is the one by Voet&Voet, which is very comprehensive:
http://www.amazon.com/Biochemistry-BIOCHEMISTRY-VOET-Donald-Voet/dp/0470570954/ref=sr_1_1?s=books&ie=UTF8&qid=1361575189&sr=1-1&keywords=voet+biochemistry

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Homologies to insect wings
All winged vertebrates have wings which are homologous to each other and to the forelimbs of the non-winged vertebrates. But what about insect wings? Are all insect wings homologous, and are there any homologies between insect wings and any vertebrate limbs?

Insects and vertebrates are extremely distantly related: they're on opposite sides of the oldest split among bilaterally symmetric animals.  Their most recent common ancestor lived in the pre-cambrian and was almost certainly worm-shaped with no limbs at all.  There's no way that insect wings are homologous to any body parts of vertebrates.
The evolution of insect wings is a somewhat difficult topic, because it happened 350 million years ago in animals that do not fossilize well.  Wikipedia discusses several possible theories for what parts of non-winged insects are homologs of insect wings.  Currently the situation does not seem to be resolved.

Insect wings (and legs) and tetrapod limbs are analogous structures. Insects are protostomes, whereas vertebrates are deuterostomes; both lineages separated in the Precambrian from something resembling a worm (some Ediacaran organisms, such as Kimberella, have been proposed to be protostomes, whereas some others, such as Burykhia, are tentative tunicates, which are the closest living relatives of vertebrates). The arthropod ancestors of insects evolved legs in the Cambrian, whereas tetrapod limbs evolved from fins (among tetrapodomorphs, via a Tiktaalik-like stage) in the late Devonian, which themselves evolved from folds (the pectoral fins first evolved within ostracoderms in the late Cambrian or Ordovician, whereas the pelvic fins arose in jawed fish in the Silurian). The origin of insect wings is still largely unknown, but the point is that they aren't homologous with vertebrate limbs/fins.

It would be great if you could add some references.

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How does protein help to cure wound?
I understand that the protein helps to repair body tissues. If I increase the intake of protein, would it help to cure the wound more quickly? I would like to know how does the protein reaches the wound and how does it help to heal?

There are thousands of different proteins in our body, some will make a wound heal, some will not make a difference, some could make the situation even worse, you cannot generalise.

Do you mean it is impossible to know and intake those proteins that heal wound?

I am just saying that speaking about "the protein" is not meaningful, as there is not just one type of protein. Also, proteins taken through food do not enter the body as such, but are first destroyed to their components (called aminoacids) in the stomach and the intestine. See Armatus answer for example of proteins produced by the body to help wound healing.

This question seems to be based on some fundamental misunderstanding, there are hundreds of thousands of different proteins. If you're interested in specific aspects of wound healing I recommend you to start with a basic biology textbook first.

Saying protein in general helps to heal wounds is a very far step. Different proteins are essential for nearly every process that happens anywhere in your body.
There is a range of proteins which is required specifically for wound healing. The first step of wound healing is blood clotting in order to close wounds. This uses several so-called clotting factors, all of which are proteins. Some of these help the platelets (small cells in the blood) stick to the walls of the blood vessels which have been damaged, others are responsible for forming a tight clot around them to make sure no more blood leaks out. Most clotting factors also require vitamin K for their production.
The next step is wound healing. This involves several cell types gathering at the wound and laying down what is called connective tissue, a network made mostly of proteins. Cells of the skin will need to replicate themselves in order to close the wound, and they will require lots of proteins for this.
Protein reaches all cells of the body from the intestines via the blood flow.
Eating a diet high in protein would surely not be a bad thing to do - your body needs it everywhere. But it is important that you consume it mixed with healthy amounts of carbohydrate (needed for energy) and fats (needed for many structures and hormones).


text:
Significance of basal lamina for outer layers of epithelium
In stratified (not pseudostratified) epithelia such as the epidermis, what purpose does the basal lamina serve for the outer layer cells which do not even stand in contact with it?
Also, how do these cells attach, all just through tight junctions to lower layers?

The basal lamina, a specialised type of extracellular matrix (ECM) that differs between cell types, acts as a base for stratified epithelia cells to layer on top of and therefore has a supportive role as well as providing a base for attachment (for the layer of cells immediately on top of it) 1. Layers of epithelial cells on top of further strata of similar cells with no differing tissue composition underneath would have no support and cell types would be able to mix freely within tissues. The different cell types within tissues are kept seperate by this ECM to maintain areas for specific functions. The importance of this can be seen through studying epithelial cancers, where the epithelial cell layer breaks through the entire basement membrance and invades the surrounding tissue. This can cause massive disruption of tissue function.
Yes, it seems that the layers of cells are attached by various junctional complexes, the desmosomes (maculae adherentes) being the most abundant for stratified epithelia.
Referenes
1 http://www.histology.leeds.ac.uk/tissue_types/connective/con_basal_lam.php


text:
Is there a free alternative to Gelcompar for comparing banding patterns across multiple gels?
In order to run my microbial community samples from my experiments through DGGE, I was required to use multiple gels.
Thus it is necessary to compare banding patterns across more than one gel.  This means that I need some way of assessing whether the 4th band on gel #1 is the same OTU as the 4th band on gel #2.
The industry standard for this procedure seems to be the Gelcompar software.  Unfortunately this software is greater than $10,000 and is proprietary (thus, not open science friendly).
Does there exist a free (ideally as in speech and beer) alternative to Gelcompar?

Do you have any programming skills? Because ImageJ immediately comes to mind. You'd just have to modify a little the already existing gel tools...

I second the ImageJ recommendation. It's already well setup for gel analysis, and people do use it for DGGE (e.g http://www.springerimages.com/Images/LifeSciences/1-10.1007_s10482-007-9143-9-0)

Here's an ImageJ mailing list entry about DGGE... http://imagej.1557.n6.nabble.com/gel-analysis-td3703740.html

Phoretix 1D Pro is a cheaper alternative and yealy licenses are available

Try this one
Pavel, A. B. & Vasile, C. I. PyElph - a software tool for gel images analysis and phylogenetics. BMC Bioinformatics 13, 9+ (2012).
You can download here
http://sourceforge.net/projects/pyelph/


text:
Finding the number of chromosomes of an organism
For a school project I need to find the number of chromosomes of an organism (specifically the adelie penguin, Pygoscelis adeliae). After several internet searches and a look through the encyclopedia at school, I am unable to find a definite answer to this question. Sources on the internet claim anything from 38 to 96 for diploid cells (with none of them citing a trustable study).
Is there any database that records the chromosome number for organisms?
Also, if this information is unavailable, what is the best way to estimate this value? On the Wikipedia article for number of chromosomes for various organisms, it listed the value for some birds, most of them in the 70-80 range. Is it safe then to assume that the number for penguins in general would be somewhere in this range?
Thanks.

No, you can't assume that penguins will have a similar number of chromosomes. If the sources you find say 38 and 96 for diploid cells, what's the contradiction? The only information missing there is how many sex chromosomes.

Answer
An comprehensive online database of the chromosome numbers of all living species most likely doesn't exist. This Wikipedia article is the best and most complete reference comprising animals that I can personally find on the internet.
This source in Spanish, which I've translated with Google Translate reads:

Canedo Delgado (1999) performed the karyotype description of the three species of the genus Pygoscelis , noting that there is a high homology both numerically and morphologically: Pygoscelis antarctica presented 2n = 92, Pygoscelis papua 2n = 94 and Pygoscelis adeliae 2n = 95 in females and 2n = 96 in males.

Also, note that chromosome number cannot be "guessed" or "assumed" for closely-related species. As shown above, the three Pygoscelis species have a high homology, but have very different chromosome numbers.
The other chromosome number you found for the species (38) is actually that of the Emperor penguin, as a simple Google search shows.

References

Ledesma, Mario A., T. R. O. Freitas, J. Da Silva, Fernanda Da Silva, and R. J. Gunski. “Descripción Cariotípica De Spheniscus Magellanicus (Spheniscidae).” El Hornero 18, no. 1 (August 2003): 61–64.

Since you didn't specify animals, I will add here for anyone coming from google that plant chromosome numbers are stored in the Index to Plant Chromosome Numbers.
I would be surprised if such a database exists for animals (except maybe insects) as historically C-numbers of plants and other cytogenetics were important for taxonomy (and still is important), whilst this was not the case so much in zoology.


text:
Is sexual reproduction outside the same biological family possible? Has it ever occured successfully?
Are there any examples of two species taxonomically classified in different biological families that have successfully hybridized and produced viable offspring? If not, is there an example of where reproduction occured with non-viable offspring?
To be clear, I mean regular sexual reproduction that could occur in the natural world outside a lab. Even so, I'd be curious to know if it could even occur in a lab without direct genetic manipulation.
For example, grolar bears which are ursid hybrids between different species in the Ursus genus are known to exist. Also ursid hybrids between bear species in different genuses have been produced in captivity (sloth bear Melursus ursinus x Malayan sun bear Ursus malayanus and sloth bear x Asiatic black bear Ursus thibetanus). Would an extra-familial hybridisation be possible? Would this be more likely in the plant kingdom?
This question is inspired by a separate question on the Gardening SE which hints at a general lack of understanding of the genetic similarity required for cross-pollination in plants. It made me wonder whether there are any exceptions to the general assumption that extra-familial hybridisation is impossible.

Following the definitions of hybrid and of sexual reproduction, one could consider Horizontal Gene Transfer and answer YES to your question with the case of the photosynthetic sea slug for example.

I should have been more specific to limit this to gene transfer/recombination occurring by sexual reproduction (i.e. vertical gene transfer) but thanks for the point.

One of the problems is that "Family" and really any taxonomic designation are fuzzy. We often don't even really know where to draw the line between two species, even in animals, where such things are relatively easy. Since none of the taxonomic designations tell us anything about genetic distance except "the two taxa are genetically different from each other", any examples of inter-familial hybridization won't tell you anything about the general likelihood of such an occurrence...

A more valuable question might be "What is the maximum genetic distance at which hybridization by sexual reproduction has been observed?" And of course, the answer to that is, "I don't know" :P. Which is why this is a comment and not an answer.

@ChinmayKanchi As stated, there is a practical purpose behind the question, not merely a completely idle wondering. A new gardener without much backgrounding in biology wants to avoid hybridisation in her vegetable patch. How do you give simple instructions on avoiding it? For the lay-person the problems of taxonomic fuzziness are of zero interest. She just has labels with the species written on. Based on the single answer, I'd tell her first only be concerned about inter-genus and inter-species hybrids and then on how to prevent such cross pollination.

Yes, and as I said, single examples don't allow you to draw any conclusions about the general case. Will species x hybridise with species y is the appropriate question to ask in this case.

@Lisa My point is that even when you say hybrid via sexual reproduction you do not exclude Horizontal gene transfer. There are so many different way of reproducing sexually that our definitions are usually quite broad. But your question is interesting, I just thought it was worth stating horizontal gene transfer as this process fits in the definitions of sexual reproduction.

Interfamilial hybrids have never, to my knowledge, been recorded occurring naturally (without human intervention).
In plants, somatic inter-familial hybrids have been produced for a wide variety of species pairs in the lab (e.g. between carrot and barley; Kisaka et al. 1997).
In animals, there are some historical reports of hybrids between chickens (Mathis & MacDougald 1987) or peafowl (Serebrovsky 1929), both in Phasianidae, and guineafowl (in Numididae). The animal example meets your condition of being outside the lab, although they were produced by breeders.
Refs

Kisaka, H., Kisaka, M., Kanno, A. & Kameya, T. (1997) Production and analysis of plants that are somatic hybrids of barley (Hordeum vulgare L.) and carrot (Daucus carota L.). TAG Theoretical and Applied Genetics. 94 (2), 221–226.
Mathis, G.F. & McDougald, L.R. (1987) Evaluation of interspecific hybrids of the chicken, guinea fowl, and Japanese quail for innate resistance to coccidia. Avian Diseases. 31 (4), 740–745.
Serebrovsky, A. (1929) Observations on interspecific hybrids of the fowl. Journal of Genetics. 21 (3), 327–340.


text:
How do proteins and genes participate in learning?
I am a computer scientist that studies biology and bioinformatics.
In the last weeks, I have been trying to study new research directions, and I would like to deepen my knowledge on the role and behavior of genes and proteins in learning.
By learning, I mean the human process: the information I is absent at time T, and present at time T+1.
I would like to study more this problem, and I am wondering: how do proteins and genes behave during learning?
I have read that proteins that participate in learning are called marker proteins. Is it true? Which role do they have?
Where could I find some resources to study this fascinating problem?
Thank you very much!

The storage of memories in cells is rarely thought of on the protein level of the cell.  Cells are usually given a developmental state, but no memory.  A cell may become a liver cell, cancerous, or diabetic, but this is not memory, but a physiological change in the cell which is usually not reversible to a previous state.
For example cancer treatments are entirely focused on identifying the cancerous cells and killing them.   Internally the genomes of cancer cells often have deletions and duplications.  They are cancerous, they have not learned to be cancerous. Though not as dramatic, it is now thought that cellular differentiation which creates different types of cells is heavily influenced by epigenetic modification of the genome; the DNA is marked by methyl groups which dictates the state of the cell by modifying the gene.  This is mediated by proteins for sure, but is quite complex and not well understood at this time. Epigenetic markers can even change gene behavior between generations of offspring as well, though that is not usually called memory.
How is information stored in the brain?  This is thought to be reflected in the organization of the neurons in the brain.  There are many kinds of neurons.  They can be distinguished by the sorts of axons and dendrites that emanate from the cell body.  They can also be distinguished by the chemical variety of neurotransmitter they use (there are a score of different molecules).  So to a great extent the type of cell and the specific proteins it chooses to use to mediate information is very important.
That being said, information is currently thought to highly related to the placement of the axons and dendrites connecting the neuron to sometimes scores of other cells, sometimes touching the cell body, other times other dendrites or neurons.  As neural activity ensues, the cells will reconfigure their connections by physically moving them.
More recently, investigators have tried to understand the genes which internally modulate the neural signals within the cells.  This nobel prize lecture discusses how the CREB/MAPK pathway can modulate Long Term Potentiation - the shape of the neuron response to a signal over time (days or hours).
Taken as a whole, you can see that memory is likely to be stored on several levels at once - the kinds of cells (dictated by differentiation) involved, structural arrangement of the neurons (axons and dendrites connecting to various cells and places on cells), as well as internal signaling circuitry that generates and modulate the electrical and chemical activity within the cell.
"Marker protein" only refers to a protein that you can follow to see some sort of activity in the cell. A typical example is Green Fluorescent Protein, which is colored, fused with a protein of interest.  It has no specific meaning regarding learning I think.

Thanx, interestin' answer. Could you indicate to me some online resources to deepen these themes?

I would choose just one of these angles to take up first.  Here's an online MIT class on learning and neuroscience http://ocw.mit.edu/courses/brain-and-cognitive-sciences/9-03-neural-basis-of-learning-and-memory-fall-2007/

Right now the neurophysiology of memories and feelings are hot and doing big things.  Here is a blog post on erasing a fear memory in a mouse. http://cellularscale.blogspot.com/2012/04/erasing-memories-cell-by-cell.html

Thanks again. May contact you privately for further detail discussion? Here's my address davide.chicco(AT)gmail.com

If you're interested in understanding the maintenance of state, history, and information, I would look at hysteresis. The classic biophysics model for studying hysteresis has been the Lambda phage which has been extensively detailed in Mark Ptashne's A Genetic Switch


text:
What are the units of Q10 (temperature sensitivity)?
$Q_{10}$ is the increase in a rate (e.g. activity of an enzyme) observed with a 10° temperature increase.
According to Wikipedia:
$$Q_{10}=\left(\frac{R_2}{R_1}\right)^{{10}/\left({T_2-T_1}\right)}$$
It is apparent that the units of $R$ (e.g. $mol/g/s$) cancel out, but what about the units of temperature? Does $Q_{10}$ have units? It seems the units would be "per 10 °C", but it is not clear how this comes from the referenced equation

Figure. A schematic diagram showing the effect of the temperature on the stability of an enzyme catalysed reaction. The curves show the percentage activity remaining as the incubation period increases. From the top they represent equal increases in the incubation temperature (50 °C, 55 °C, 60 °C, 65 °C and 70 °C).
The $Q_{10}$ is a unitless number, that summarizes the effect of raising temperature 10°C on the rate of a chemical reaction. A $Q_{10}$ of 2.0 suggests that raising the temperature of a system by 10 °C will effectively double the rate of the reaction. This value would be expected for most chemical reactions occurring within normal physiological temperatures.
Mathematically, $Q_{10}$ can be represented by the following expression:
$$Q_{10}=\left(\frac{k_2}{k_1}\right)^{\frac{10}{t_2-t_1}}$$
$t_2$ = higher temperature
$k_2$ = rate at $t_2$
$t_1$ = lower temperature
$k_1$ = rate at $t_1$
Usually the temperature difference is about 10 °C, then you can simplify the equation
$$Q_{10}=\left(\frac{k_1}{k_2}\right)^{\frac{10}{10}}=\frac{k_1}{k_2}$$
Edit: You can easily calculate $k$ form Arrhenius equation
$$k=Ae^{\frac{-\Delta G^*}{RT}}$$
where $k$ is the kinetic rate constant for the reaction, $A$ is the Arrhenius constant, also known as the frequency factor, $-\Delta G^*$ is the standard free energy of activation ($kJ/mol$) which depends on entropic and enthalpic factors, $R$ is the gas law constant and $T$ is the absolute temperature.

how do you calculate k, are the curves in the figure something like e^{-kt}?

Here k is a rate constant like R in your wikipedia example, and for the figure the curves show the percentage activity remaining as the incubation period increases.

But how do you estimate the pre-exponent factor A?

My understanding of Q10 it that it is the ratio of the rate of a chemical reaction at a specified temp to the rate of a chemical reaction 10 degrees higher.  For example if the rate of an enzyme-catalysed reaction at 37 C is twice that at 25 C, then can speak of a Q10 being equal to 2.  Q10 makes no assumptions about the underlying mechanism which, for an enzyme catalysed reaction, is likely to be complex, and to involve temperature effects on multiple rate constants (both first-order and second-order).  I find your diagram of (first-order) decay curves misleading. These may be used to ...

calculate the half-life of an enzyme at different temperatures, but surely have nothing to do with Q10?

This is a nice example of mathematical sloppiness which is more often present in textbooks on biology than on chemistry or physics where perople are more careful about dimensional analysis*.
The correct form of equation (with your notation) is
$$Q_{10} = \left(\frac{R_2}{R_1}\right)^\frac{10\,^\circ\mathrm{C}}{T_2-T_1}.$$
From this form, it is clear that the units of temperature cancel out, and that  $Q_{10}$ is therefore unitless.

* For example, exponential function – such as the one present in the equation for $Q_{10}$ – cannot take units as an input, only dimensionless numbers.


text:
Pipetting damage to cells
I'm curious how much damage is potentially inflicted by shear stress by pipetting. I know that syringes used for stem cell injection can cause a lot of damage. However, to what extent does this happen with P20 and P200 pipette tips? Understandably the shear modulus of bacterial cells is significantly different from that of cancer cells, which will be different from that of stem cells.

It might be possible to compare P200 with P20 on the cheap (anybody up for a crowd-sourced experiment on HeLa or E. coli?), but I suspect you actual question asks for absolute numbers, and is therefore almost impossible to answer. It is hard to envisage any non-pipette method to deliver 100% viable cells, and even harder to think of alternatives (measure free DNA after pipeting? how can that be converted to cell counts?). User137 suggests something decent, but still short of absolute. In the absence if evidence, all the answers you will receive are bound to be speculative "expert opinion".

This is an excellent question, I have been training people to culture cells for about 12 years and students have a hard time grasping this and appreciating the importance etc.
What cells are usually experiencing during pipetting is analogous to a crowd of people trying to fit through the doorway of a building. Shearing during pipetting  is certainly a legitimate concern in cell culture. You will notice its negative effect on viability most explicitly when pipetting cells in freezing
 medium (containing DMSO) following a thaw. Until their DMSO concentration drops their membranes are weaker & more fluid. That's why you pipette the frozen cells drop-wise to the fresh medium, to be especially gentle at this point.
Prokaryotic cells such as the above mentioned TOP10 cells are treated with Calcium chloride and glycerol which has essentially the same effect on their walls and membranes. Hence pipetting should be delicately performed after thawing these cells as well.
With that being said, if you compare the sensitivity of prokaryotic and eukaryotic cells to shearing, eukaryotic cells are profoundly more sensitive.
For individuals using competent bacteria for sub-cloning and other routine uses, killing a small percentage of of your cells is not that important. However if you are using the transformation to generate cDNA libraries it's very important that you have a titer sufficiently representing the transcriptome the library is composed of.
In these instances using a more premium competent cell, adhering to correct temperatures and minimizing pipetting is essential. This is why many are taught to swirl the DNA the with the competent cells, rather than the harsher alternative: pipetting up-and-down.
The four most important factors that contribute to cellular shearing are, and in order form most to least contributory:

Diameter of the bore in the pipette tip, the smaller the more shearing.
Speed at which the suspension is passing through the opening of the tip. The faster the more damaging.
Size and rigidity of the cell. Larger cells are more prone to damage.  Cells with a murein wall are less prone to damage.
Concentration of cells. Cultures that are more concentrated are more prone to damage.

Because the make up if the cell itself is so influential on the amount of damage, and because of the enormous variety of cells; designing a representative experiment to assess damage would be very difficult and  laborious.
Finally,  the variety of tips and seriologicals is also enormous. However if one were to attempt to assess this it could be done:
Choose a representative variety of cell lines, choose a representative variety of pipettes. One would probably want to use a robotic pipette to be able to  evaluate incrementally assigned speeds and pressures. Look at different culture concentrations,  phases of the growth curve, time between pipetting and analysis, distance between the exiting fluid and the culture etc, etc.
I think a very successful analysis method would be using propidium iodide and FACS.
After your experiment which will cost a lot of time and $, I think you will find common sense rules: keep pipetting to a minimum and use wider tips whenever possible.

This is a good explanation but does not actually give a numerical representation of percent death to no harm caused by the palleting.

Good point Here I will  rephrase as it seems to be getting quite a number votes

Won't the material with which the pipette is made affect the cell too? I would imagine cell membranes having different affinity to different materials

@CRags certainly yes but really minimal.

It's an easy experiment to do. Take your cells aliquot them into 10 microfuge tubes, and pipette each suspension increasing amount of times, stain with trypan blue and count.
The most important factors will be which pipette-type you use; I would expect a p1000 to cause more damage then a p200 then a p20 due to velocity of the fluid. Also the most important factor will be the skill of the scientist, if you pipette slowly it should decrease stress as opposed to pipetting quickly.
In my experience it depends on the pipette-type and the skill of the operator. The only way to answer this for you is to try it empirically.

Well, then that will heavily be based on operator error. Anecdotally, I've heard that it is the other way; a P1000 would causes less damage than a P20.

Artem is right: the only way to say is empirically. The P1000 will influence the cell damage likely because of the velocity. In contrast, the P200 and P20 could give some damage due to the narrow tip hole.

Give it a try and post the results. I do believe that operator skill is the single most important factor.

We used to use a peristaltic pump to plate HepG2 cells into 384 and 1536 plates. When we moved to primary hepatocytes the pump killed too many and had to move to hand plating with an 8 channel pipette. So cell type matters a lot.

Naw this isn't going to measure the correct....just naw

Anecdotally I have not observed any cell death upon pipetting of E. coli DH5alpha or TOP10, however as competent cells, mixing by pipetting up and down is discouraged due to the compromised cell wall.

Good pointIt's pretty hard to kill bacteria mechanically  period, the competent cells are more sensitive though and concern comes when  building cDNA library's mostly as you need a very representative number of colonies

This is a fine observation.

This question would be better served in the physics se or chemistry. I don't think we have a generic engineering where fluid dynamics could be described in a different method than physics but if we did it should also be answered there.
Indeed the osmotic or liquid pressure in and of itself would cause changes possibly damages to the cell. Then other eexothermic and endothermic reactions to the chemicals due to force of impact like a chem or friction burn.
I'm sure the other requirements of conservation of energy which I half-hazardly ignored.
I found this interesting paper which focuses on the shear stress in general.

Pipetting causes shear stress and elevation of phosphorylated stress-activated protein kinase/jun kinase in preimplantation embryos.
Xie Y1, Wang F, Puscheck EE, Rappolee DA.
Shear stress at 1.2 dynes/cm(2) induces stress-activated protein kinase/jun kinase phosphorylation that precedes and causes apoptosis in embryos (Xie et al., 2006b, Biol Reprod). Pipetting embryos is necessary for many protocols, from in vitro fertilization to collecting embryos prior to analyzing gene expression by microarrays. We sought to determine if pipetting upregulates phosphorylated MAPK8/9 (formerly known as stress-activated protein kinase/jun kinase/SAPK/JNK1, 2). We found that phosphorylated MAPK8/9, a marker of MAPK8/9 activation, is upregulated in a dose-dependent manner by pipetting. Whereas embryos with the zona pellucida removed were more sensitive to stress-induced lethality mediated by 1.2 dynes/cm(2) shear force, phosphorylated MAPK8/9 was induced at lower numbers of pipet triturations in hatched embryos at E4.5. E4.5 embryos were more sensitive to induction of MAPK8/9 than unhatched embryos at E2.5 or E3.5. E3.5 embryos also showed a pipetting dose-dependent induction of FOS protein (formerly known as c-fos), a marker of shear stress in many cell types. Phosphorylated MAPK8/9 measured in ex vivo embryos from E1.5 to E4.5 were expressed at low levels. Embryos that had been pipetted sufficiently to induce phosphorylated MAPK8/9 and FOS had the same number of cells as untreated embryos 24 hr later. This suggests that rapid phosphorylation of MAPK8/9 due to transient shear stress does not mediate long-term negative biological outcomes. But, it is possible that techniques requiring multiple handling events would induce MAPK8/9 and cause biological outcomes or that other biological outcomes are affected by low amounts of transient shear stress. This study suggests that embryo handling prior to experimental measurement of signal transduction phosphoproteins, proteins and mRNA should be performed with care. Indeed, it is likely that shear stress may cause rapid transient changes in hundreds of proteins and mRNA.

@rhill45 yeah the question was about cell shear stress damage during pipetting..the other answered seemed to buy into the only damage coming from the pal tip..but i wanted to point out that the shear stress from the pipetted liquid is equally likely to damage/destroy the cell.

@rhill45 also if your going to learn php you should invest time in asp because many industries see saw between the two.

Shear stress $\tau$ in this small sizes is usually measured in dyne/cm2 or N/m2 = Pa. The equations betweeen them: $1dyn/cm^2 = 10^{-5}N/cm^2 = 0.1N/m^2 = 0.1Pa$.
What kind of damages zygotes can suffer by pipetting?

Using scanning electron microscopy, we found open holes on the surface
  of lysed eggs, indicating failure of the plasma membrane to reseal
  after microinjection. No holes were seen in unlysed eggs, but many of
  them had membrane alterations suggestive of healed punctures.

1987 - Zygote viability in gene transfer experiments

Even a small 1.2 dyn/cm2 shear stress induces apoptosis by pipetting zygotes. So zygotes have their critical shear stress level by 1.2 dyn/cm2 and pipetting involves greater forces than 1.2 dyn/cm2.

Shear stress at 1.2 dynes/cm2 induces stress-activated protein
  kinase/jun kinase phosphorylation that precedes and causes apoptosis
  in embryos (Xie et al., 2006b, Biol Reprod). Pipetting embryos is
  necessary for many protocols, from in vitro fertilization to
  collecting embryos prior to analyzing gene expression by microarrays.
  We sought to determine if pipetting upregulates phosphorylated MAPK8/9
  (formerly known as stress-activated protein kinase/jun
  kinase/SAPK/JNK1, 2). We found that phosphorylated MAPK8/9, a marker
  of MAPK8/9 activation, is upregulated in a dose-dependent manner by
  pipetting.

2007 - Pipetting causes shear stress and elevation of phosphorylated stress-activated protein kinase/jun kinase in preimplantation embryos

The critical shear stress level is somewhere between 0.01 and 1000 dyn/cm2 by animal cells depending on the cell type and species. (I think the average is somewhere about 50 dyn/cm2, but it is very hard to differentiate between articles mentioning critical shear levels and most lethal shear levels, so the range and the average might be lower.) The death constant (1/h) increases exponentially by increasing the shear stress.

An apparatus for the detailed investigation of the influence of shear
  stress on adherent BHK cells was developed. Shear forces between 0.0
  and 2.5 N m−2 were studied. The influence on cell viability, cell
  morphology, cell lysis, and cell size was determined. Increasing shear
  forces as well as increasing exposure duration caused increasing
  changes in cell morphology and cell death. A “critical shear stress
  level” was determined.

1992 - Determination of a “critical shear stress level” applied to adherent mammalian cells

Shear stress related damage to a mouse hybridoma was examined by
  Abu-Reesh and Kargi under laminar and turbulent conditions in a
  coaxial cylinder Searle viscometer. Cells were exposed to 5 to 100
  N/m2 shear stress levels for 0.5 to 3.0 h. At a given shear stress and
  exposure time, turbulent shear was much more damaging than laminar
  shear as also reported in the past for protozoa and plant cells. Under
  turbulent conditions, damage occurred when shear stress exceeded 5
  N/m2. Respiratory activity of the cells was damaged earlier than the
  cell membrane, thus implying transmission of the stress signal to the
  interior of the cell. Cell damage followed first-order kinetics both
  in laminar and turbulent environments. For turbulent shear stress
  levels of 5 to 30 N/m2, the death rate constant (kd) increased
  exponentially with increasing stress level; the kd values varied over
  0.1 to 1.0 1/h.

2001 - Hydrodynamic Damage to Animal Cells

Subconfluent endothelial cultures continuously exposed to 1–5
  dynes/cm2 shear proliferate at a rate comparable to that of static
  cultures and reach the same saturation density (≃ 1.0–1.5 × 105
  cells/cm2 ). When exposed to a laminar shear stress of 5–10 dynes/cm2
  , confluent monolayers undergo a time-dependent change in cell shape
  from polygonal to ellipsoidal and become uniformly oriented with flow.
  Regeneration of linear “wounds” in confluent monolayer appears to be
  influenced by the direction of the applied force. Preliminary studies
  indicate that certain endothelial cell functions, including fluid
  endocytosis, cytoskeletal assembly and nonthrombogenic surface
  properties, also are sensitive to shear stress. These observations
  suggest that fluid mechanical forces can directly influence
  endothelial cell structure and function.

1981 - The Dynamic Response of Vascular Endothelial Cells to Fluid Shear Stress

Shear stress above 0.25 dyne/cm(2) resulted in dramatic loss of
  podocytes but not of proximal tubular epithelial cells (LLC-PK(1)
  cells) after 20 h.

2006 - Podocytes are sensitive to fluid shear stress in vitro

A series of careful studies has been made on blood damage in a
  rotational viscometer. Specific attention has been focused on the
  effects of solid surface interaction, centrifugal force, air interface
  interaction, mixing of sheared and unsheared layers, cell-cell
  interaction, and viscous heating. The results show that there is a
  threshold shear stress, 1500 dynes/cm2, above which extensive cell
  damage is directly due to shear stress, and the various secondary
  effects listed above are negligible.

1972 - Red Blood Cell Damage by Shear Stress

The shear stress threshold of some dinoflagellates (microalgae) is
  even lower than that of erythrocytes (0.029 N/m2). For example, a
  continuous laminar shear stress level of only 0.0044 N/m2 (equivalent
  to a shear rate of 2.2 1/s) has proved lethal to the dinoflagellate
  Gonyaulax polyedra.

Upstream Industrial Biotechnology

Other cell types are not necessary as sensitive as animal cells and they don't necessary react with apoptosis (about 10 dyn/cm2) to shear stress, so you have to use necrotic (about 5000 dyn/cm2) forces to destroy them :
cell type                       size                shear sensitivity
microbial cells                 1-10μm              low
microbial pellets/clumps        up to 1cm           moderate
plant cells                     100μm               moderate/high
plant cell aggregates           up to 1-2cm         high
animal cells                    20μm                high
animal cells on microcarriers   80-200μm            very high
fungi cells                     2-10μm              moderate/high

Table 1 - shear sensitivity by cells types
Bioprocess Engineering Principles: table 8.6 - Pauline M. Doran
1996 - Role of hydrodynamic shear in the cultivation of animal, plant and microbial cells
1988 - Effect of shear on the viability of plant cell suspensions
2004 - A quantitative analysis of shear effects on cell suspension and cell culture of perilla frutescens (plant) in bioreactors
2009 - Shear Sensitivity - the full text probably contains all the numbers

Results show that Chinese Hamster Ovaries and Human Embryonic Kidney
  cells will enter the apoptotic pathway when subjected to low levels of
  hydrodynamic stress (around 2.0 Pa) in oscillating, extensional flow.
  In contrast, necrotic death prevails when the cells are exposed to
  hydrodynamic stresses around 1.0 Pa in simple shear flow or around
  500 Pa in extensional flow.

2009 - Induction of mammalian cell death by simple shear and extensional flows

The shear sensitivity is not determined only by cell type and species, there are many other factors involved:

type of cell and species
composition and thickness of cell wall when present
size and morphology of cell
the intensity and nature of shear stress, whether turbulent or laminar, or associated with interfaces (e.g. during bubble rise and rupture)
growth history, both short-term (e.g. starvation) and long term adaptation
growth medium (trace elements, vitamins, carbon and nitrogen sources)
growth rate
growth stage
type and concentration of shear protective agents if present

Cells can be very sensitive to shear stress caused by turbulent flow, while not so sensitive to shear stress caused by laminar flow.

On the basis of laminar flow viscometriy measurements, a critical
  shear stress level of 80-200 N/m2 has been suggested for Morindata
  citrifolia cells.
... while for Daucus carota a shear stress level of 50 N/m2 has been
  associated with cell damage. In other study, carrot cells in a laminar
  flow Couette viscosimeter lost the ability to grow and divide in the
  shear stress range of 0.5-100 N/m2. The intracellular enzyme activity
  was impaired at shear stress levels above 3000N/m2, but significant
  lysis did not occur until a shear stress level of 10.000 N/m2 applied
  over a prolonged perioud (>1h).
In contrast to the behavior in laminar flow, the cells were quite
  sensitive to turbulent impeller agitation. Impeller tip speeds of ~1.1
  m/s lysed a significant proportion of the cells within 40min.

Cell and Tissue Reaction Engineering
Upstream Industrial Biotechnology

The bubble damage is severe (1000 cells by a single 3.5mm size bubble) because of the cell adherence to the interface of the bubble and the strong forces involved (>1000 dyn/cm2 by stirred bioreactors). The adhesion and so the damage can be reduced with surfactants.

2004 - Quantitative studies of cell-bubble interactions and cell damage at different pluronic F-68 and cell concentrations.
2004 - Surfactant Reduction in Embolism Bubble Adhesion and Endothelial Damage

It is proposed that when cells are either attached to, or very near, a
  rupturing bubble, the hydrodynamic forces associated with the rupture
  are sufficient to kill the cells.
All experiments were conducted with Spodoptera frugiperda (SF-9)
  insect cells, in TNM-FH and SFML medium, with and without Pluronic
  F-68. Experiments indicate that approximately 1050 cells are killed
  per single, 3.5-mm bubble rupture in TNM-FH medium and approximately
  the same number of dead cells are present in the upward jet. It was
  also observed that the concentration of cells in this upward jet is
  higher than the cell suspension in TNM-FH medium without Pluronic F-68
  by a factor of two. It is believed that this higher concentration is
  the result of cells adhering to the bubble interface. These cells are
  swept up into the upward jet during the bubble rupture process.
  Finally, it is suggested that a thin layer around the bubble
  containing these absorbed cells is the “hypothetical killing volume”
  presented by other researchers.

1994 - Quantification of damage to suspended insect cells as a result of bubble rupture

For a hybridoma line, reported that exposure to laminar shear stress
  (208 N/m2) in unaerated flow in a cone and plate viscometer led to
  substantial loss in cell count and viability within 20 min. At a
  constant 180 s exposure, increasing shear stress over 100-350 N/m2
  linearly enhanced cell disruption, with >90% of the cells being
  destroyed at 350 N/m2 stress level. Shear stres levels associated with
  bubble rupture at the surface of a bioreactor may range over 100-300
  N/m2. These values are remarkably consistent with shear rates that
  damaged hybridomas in unaerated laminar flow experiments.

Upstream Industrial Biotechnology

Smaller hole pipettes cause more damage.

We also examined aspects of the gene transfer procedure that might
  influence survival such as the size of injection pipettes and their
  taper relative to zygote diameter, possible toxicity of the injection
  medium, the timing of injection, and immediate vs. delayed pipette
  withdrawal. The only factors that significantly affected cell
  viability were pipette size and taper, and timing of injection in
  relation to first cleavage. This suggests that zygote viability
  correlates inversely with the size of the hole produced by the
  injection pipette and that damage to the membrane is less successfully
  repaired as the fertilized egg readies itself for division.

1987 - Zygote viability in gene transfer experiments

It is hard to find anything about the level of shear stress by pipetting. It can be certainly more than 1 dyn/cm2. It has a short duration (at most a few seconds). I think the following factors can influence the shear stress levels by pipetting:

pipette type
flow speed (faster flow can be more likely turbulent)

negative pressure by suction
hole size (bigger hole can reduce flow speed)
liquid viscosity

bubble formation

Probably more factors are involved but I am not a pipetting expert. ;-) I agree with the others, it surely depends on the personal skills e.g. an amateur can create huge bubbles by pipetting, which can kill a lot of cells by formation and disruption...
I agree with Artem that this is an experiment to do especially if the result is important for you. What you need to create a model about pipette damage, are the shear stress levels by pipetting and the critical shear stress levels of the cells. I think it is hard to design and experiment in which you can measure the shear stress levels in your pipettes and there is no flow model for pipetting as far as I know, so it can be a good topic for a thesis or a diploma work.

I know this is a two-year-old thread, but I though I would post this anyway in case someone else is searching for this answer like I was tonight. This article cited below doesn't discuss pipette tips vs needles specifically, but it does discuss the difference in effects of tapering vs cylindrical needles on cell damage. Unfortunately, the math in the paper is a bit beyond me (I'm a doctor, not an engineer, and they didn't cover this stuff in medical school), but they found that with cylindrical needles result in approximately 5x the amount of cell death compared to a tapered needle at any given flow rate, and approximately 6-8x the amount of cells damaged. This was likely due in part to the need for higher pressures to increase flow rates in cylindrical needles compared to tapered needles and variations in shear due to the geometries. While a tapered needle is not identical to a plastic pipette tip, the geometries are comparable.
Biotechnol Prog. 2011 Nov-Dec;27(6):1777-84. Effect of needle geometry on flow rate and cell damage in the dispensing-based biofabrication process. Li M1, Tian X, Schreyer DJ, Chen X.
http://onlinelibrary.wiley.com/doi/10.1002/btpr.679/full

I have a real life biological example.
simplified experiment setup:
ex vivo purified B cells undergo 3 washes in PBS (spin and resuspend), then they are incubated in vitro for 24 hrs and analyzed by flow cytometry using Acqua Zombie and PI for dead cell exclusion.
Experiment 1: pipeting after washes using 1ml tip
Experiment 2: pipeting after washes using 10ml pipette
Cell survival as analyzed by flow cytometry:
Experiment 1: 9.96%
Experiment 2: 43.9%


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Are there any organisms with larva more advanced than adult form?
Usually adult organisms are more sophisticated than corresponding larva, i. e. frogs, mosquitoes, fish. Are there species where the opposite is true?

What do you mean by "advanced" and "sophisticated"? These are qualitative.

Difficult to convey. Something sort of this quote from wikipedia about crocodiles: Crocodiles are among the more biologically complex reptiles despite their prehistoric look. Unlike other reptiles, a crocodile has a cerebral cortex, a four-chambered heart,and the functional equivalent of a diaphragm, by incorporating muscles used for aquatic locomotion into respiration (e.g. m. diaphragmaticus);

I guess I'd object to that characterization of crocs. See http://en.wikipedia.org/wiki/Evolution_of_biological_complexity

Maybe, but the characterization is still useful in clarifying the meaning of "advanced".

I mean even if crocs are not as good as wiki describes them, the I would be more than happy had a larva got listed advancements.

To add in some more complexity: There also is the - somewhat disputed - hypothesis, that larva and "adults" actually are two different animal species with one shared genome. ( http://www.pnas.org/content/106/47/19901.full )

First let me agree with the commenters that your question doesn't really make sense.  Nonetheless here's an example that you may find interesting. Arachnocampa are insects that spend almost their entire lives as larva. These larva spin silk trap lines which capture and poison prey. They can only live in windless places (wind will mix up the lines) so to lure insects into caves they glow. By contrast their imago forms are short-lived poor fliers which are unable to eat.


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What are the consequences of voluntary total celibacy?
Psychologically this might be a tough question, but in means of biology, what are the effects of total celibacy on the gonads and the nervous system concerning both man and woman in short and long term? Has there any research made in medical terms and as a bonus question, is there anything similar on other animal kingdom like deliberate celibacy?

What kinds of effects are you asking about? Changes in hormones, nervous system, organs,...?

Good point. Any effects known are on my interest. Do you think it is too wide topic then?

Possibly... most of all though I can't really imagine how celibacy would have any effect on the body apart from the brain :)

Well as far as I know, testicles are producing spermatogenesis all the time for men. What happens to that in normal sexual life compared to celibatic life for example. Maybe effects reaches also brain. I suppose there must be some implications on body.

You could rephrase the question to "effects on the gonads and the nervous system" in that case, though I'm not sure there would be any effect at all. Gonads don't normally become deficient from not being used as far as I know.

Made the change. I'd also like to know, if there is any mechanism, that actually "forces" men or why not men too to ejaculate, like for a reason to clean or refresh gonads or is this done by normal body's metabolism. And if there are any harm that celibacy could do in terms of biology. All this could be handled on answer.

I was told in my undergraduate degree that males produce sperm all the time, and that under conditions of no sexual stimulation, that sperm is excreted involuntarily every 15-16 days, at night, while dreaming. I was also told that the renewal rate of sperm is higher under regular sexual stimulation, which increases the fertility of the sperm that is excreted.

This is very interesting if true. It means that for thousands of years, monks and other ascetics who abstain from sex/masturbation have still been having fairly regular ejaculations, making the whole thing much more bearable. I always thought it seemed an inhuman feat!

If there is any research papers on public, I'd like to see them. I also happen to have opportunity to ask this question from several decades being Indian brahmacarya meaning celibate monk in few days I think. Let's see how it correlates with teachings on schools. Also this is male specific, is there counter part for similar organ behavior for females?

@Richard “monks and other ascetics” – note that the former doesn’t imply the latter. I’m suspecting that the representation of monks in The Name of the Rose is more than a little true, both now and then.

@PHPGAE: it is what is usually called a wet dream. The scientific name is Nocturnal emission and it happens in both sexes.

Site says, involuntary excretion cycle was averaged from three weeks to 5,5 weeks. High testosterone increased cycle, supposedly low testosterone decreases the cycle. Depending on that and age natural emission occurs for celibates, which can be also interpreted, that there is nothing unnatural on celibacy, because nature handles things anyway. However Indian yogi I met today said, that normally it happens about once per month if energy is not cultivated by psycho-physical exercises. He claimed full-time monks can be without ejaculating months after months, years after years no problem.

So I cannot accept the answer from that part because cycle is inaccurate and it seems there are exceptions on "law".

@KonradRudolph you're right, perhaps just "ascetics". I don't want to make any claims about the behaviour of monks...

I'm not sure how to proceed with this topic, but I made a voluntary experiment past year and decided to have a full celibate. I countered only one nocturnal flow, I should say partial, between whole 365 day test period. I think there a lot to research on this topic on academic circles. I could collect some thoughts and observations from memory, but they would be totally personal and might not help from empiric view of point. I wonder if there are peer groups, that could collect information by interviews or similar and give scientifically & statistically more interesting data...

Not entirely on your question but I think sufficiently relevant:
This paper (freely available) identified a non-causal link between ejaculatory frequency and incidence of prostate cancer.

Men were asked their age at first ejaculation, the maximum number of ejaculations ever experienced in 24 h, and to estimate the average number of times that they had ejaculated per week in their most sexually active year in each of three decades of age (i.e. third, fourth and fifth).

Leading to results indicating that:

Greater ejaculatory frequency in the most sexually active year in each of the three decades was associated with a significantly lower risk, with men in the upper quartile of ejaculatory frequency having about two-thirds the risk of those in the lower quartile for the third and fourth decade, and four-fifths the risk for the fifth. Ejaculatory frequencies in each of the decades were correlated with one another (r = 0.5–0.7). A similar finding related to the total number of ejaculations over the three decades. Those who reported an average of four to five or more ejaculations per week had two-thirds the risk compared with those who, on average, ejaculated less than three times per week.

Giles, G.G., Severi, G., English, D.R., McCredie, M.R.E., Borland, R., Boyle, P. and Hopper, J.L. (2003), Sexual factors and prostate cancer. BJU International, 92: 211–216. doi: 10.1046/j.1464-410X.2003.04319.x

This was worth of mentioning I think.


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Are there any DNA base sequences that are fully conserved between the genomes of all humans?
That is, they don't differ throughout the entire population. I understand of course that we can't DNA sequence every human, so by "fully" I mean there's an incredibly small probability of there being a mutation retained in a living individual.
Also by the genome I'm referring to the consensus of all the cells composing in the individual.
I guess my question is really, where are the crucially important sections of DNA that are simply unmodifiable without being incompatible with life?

In 2004 Bejerano et al. identified "481 segments longer than 200 base pairs (bp) that are absolutely conserved (100% identity with no insertions or deletions) between orthologous regions of the human, rat, and mouse genomes". These were found to be mostly in/around genes related to RNA processing, which is perhaps unsurprising given that it is such a primitive/inherent biological process.
Bejerano's paper has been cited over 500 times on Scopus, with numerous papers reporting variants in such regions that cause diseases such as colorectal adenocarcinomas.

So few conserved regions exist because there is plenty of redundancy in the genome; many genes functionally overlap with others, and many genetic variants are 'silent' - they have no effect on the phenotype. Having this variability is advantageous in Darwinian terms because this increases the evolvability of the species.
There are many regions of very high homology between individuals (protein-coding regions are highly conserved even between species), but there will still be natural variation; each mutations effect will be dependent on the rest of the genome. Genes work together to produce a working organism - they do not each code for a little 'bit', and therefore a change in one portion of the DNA may be 'balanced' by a change elsewhere.
It is only in 'ultra-conserved' sequences that mutations are presumably incompatible with life because the process is so finely-tuned and indispensable.

Interesting, thanks for the research link and explanation!

ahem, "very high homology"?

@bobthejoe, thanks for that constructive comment. Is the the 'very' you dislike? Or the 'high'? Or the combination of the 2 used with 'homology'? Degrees of homology are commonly used to describe the relatedness of 2 biological systems/molecules/processes... whatever.

@LukeTheDuke. Meaning that it is commonly used doesn't mean that it is appropriate. There shouldn't be degrees of homology, just homology. Yes, I am nitpicking but it is a concept that should be better enforced.


text:
Why do people have darker skin in sunnier climates?
I don't understand why darker skin is advantageous in hotter climates. Wouldn't it absorb more of the heat? I have heard that it reduces the incidence of cancer, but I would think absorbing more radiation would increase the risk?

One of the important pigments that the earlier answer hinted at is melanin.  Melanin is a brown pigment with photoprotectant properties.
As you correctly identified in your question, exposure to EM radiation (particularly UV and shorter λ waves) is damaging (indirectly) to DNA, which can cause mutations and therefore possibly cancer.  Melanin production is one of the defence mechanisms the body has evolved to deal with this threat.
When DNA is damaged by the UV-B radiation, melanogenesis (the increased production of melanin pigment) is induced.(1)  Therefore, people often exposed to more UVB (i.e. in sunnier climates) are likely to have more melanin in their skin, which makes it appear darker in colour.  It is likely to be the increased incidence of melanin proteins in your skin which leads to the formation of a tan.
Melanin and its derivatives work as photo-protectors (protecting the body from the damaging effects of ultra-violet exposure) by absorbing UV-B photons and converting them into much less damaging infra-red wavelengths (heat energy).  It does this extremely rapidly by internal conversion and extremely efficiently - efficiency in excess of 99.9% has been reported.
As the melanin removes the danger posed by the UV within a few femtoseconds (x10-15 s), the more melanin that is present in skin tissues (and consequently the darker the skin), the lesser the chance of the UV damaging molecules in the skin so the lesser the risk of developing skin cancer.

I heard one proposition that has to do with cancer, and the other side of the coin is related to vitamin D and calcium. If I remember correctly, living in a sunnier climate can affect your skin and cause cancer. The trick is to produce pigments in the epidermis so that the radiation is absorbed by the pigments and doesn't go further inside into the dermis, where it could cause DNA damage to the living dermis cells. The epidermis is constantly shedding dead cells out, so apart from absorbing more heat, there is no problem in absorbing radiation in the pigments at the epidermis level.
Having lighter skin in cloudier climates favors the absorption of sunlight, which is necessary for the production of Vitamin D, which in turn is necessary for the regulation of the levels of usable calcium in the body. Not having enough calcium is associated to all sorts of diseases.
The claims for VitD/calcium/sunlight are sometimes also associated to lactose tolerance in adults. The scene we see in pictures where someone wakes up in the middle of the night, opens the fridge and downs a gallon of fresh milk is actually not applicable to most of the human populations. We are lactose tolerant during our infancy, but for most of us, lactase production slowly shuts down when we grow up. The claim related to calcium metabolism is that human populations living in cloudier climates became adapted to lactose tolerance in adulthood so that they could make use of the calcium available in milk, and that extra calcium would contribute to a balanced calcium metabolism given that there is not much sunlight in their climates.

Totally disagree with the first paragraph of this answer. It is the skin which is most susceptible for malignancy from UV radiation. For the epidermal cells to be shed constantly it has to be produced constantly. This happens at the basal and parabasal layers where there is constant cell division occuring to replace the cells that are shed. As far as any ionising radiation is concerned it is the cells that are dividing which are most susceptible for DNA damage. The cells of the dermis are mostly quiescent and its DNA damage has far less consequence.


text:
How old does a baby have to be before it can retain memories?
For most people (my earliest memories are of perhaps when I was 2 or so) their earliest memories would be when they were over a year old.
How old does the average baby have to be before it can retain memories?
Are there any preconditions that need to be fulfilled?

I wish I had the time to do some research and give you a proper answer with references, but exams... As far as I know, the brain starts working completely even before birth (including memory function - think about it, a newborn remembers who its parents are), and you can't remember anything from before aorund age 3 because of radical rearrangements while shaping personality. If nobody answers in two weeks, I'll get back to you ;)

I'll wait. What you mentioned there about the brain working completely even before birth was where I was headed myself - Why do we seem to remember nothing from our period as a foetus? My guess was that it is a sterile environment - nothing new ever happens. Anyway, regardless of whether anybody else replies, please do post your thoughts after the exams. All the best for them!

Surely an important question. But there are different kinds of memory (classified mainly as declarative and procedural) which you don't specify exactly in your question. Wikipedia and Scholarpedia list here many known facts. I will give you some short hints and links for introduction and overview instead of pasting that stuff here.
You are probably referring to autobiographical or episodic memory, that is memorizing consciously particular events within one's own life within a context. And for this type of memory researchers agree that self-awareness seems to be a necessary precondition. The existence of this cognitive ability can be checked by the mirror test. Human infants pass this test normally around a age of 18 months (also some animals). The cognitive self develops between 21 and 24 months and marks the end of infantile amnesia.

I did indeed mean episodic/autobiographic memory, albeit the terms were not in my dictionary earlier. During the period between birth to when this self-awareness is exhibited, would it be fair to state the baby still acquires knowledge ? E.g. Self/body control (movement of limbs), cause-and-effect (crying to convey discomfort) etc. At some point such knowledge as is already acquired triggers (for want of a more appropriate word) self-awareness?

This seems like a funny interpretation to me: if self-awareness is a precondition, we're forced to conclude that many animals never retain memories (e.g. dogs). Under one definition of memory this may be true, but as I read the question it's not the definition the OP is working with.

@Everyone Your further questions are answered in the first paragraphs of the given link http://en.wikipedia.org/wiki/Memory_development, e.g. recognizing mother voice or language acquisition. What triggers self-awareness is one of the trickiest questions in science, you should open another question for this.


text:
Designing genes with DNAWorks: Maximum nonzero score?
I'm designing a gene in DNAWorks, and I'm unable to find a set of conditions that gives an "overall score" of zero (which is what I normally insist on). People that have used DNAWorks: what's the highest nonzero score you've been able to successfully assemble?

Can you give us more information on what you are trying to assemble (size, length of overlap, length of oligos) and how you plan to assemble it?

The gene is ~600 bp in size. I'm flexible on the oligo length and overlap length, but I was thinking something like 50-60 bp oligos and 15 bp overlaps. I'll assemble it by Gibson assembly directly into the vector backbone, but the part is designed so that I can also assemble it the standard way: first assembling the gene by PCR and then ligating it into the vector. Thanks!

@GerganaVandova, I think that the question is trying to  get at the design portion and not the actual building portion of gene assembly.

@bobthejoe I am trying to say that the design portion is not the bottleneck.

You might want to read Gibson's paper on the step-wise assembly of the mouse mitochondrial genome (1):

He started with 60b long oligos with 20b overlap, as he assembled 5 of those 60-mers into a backbone, obtaining 384b fragments. On the next step, he joined 5 of those 384mers, obtaining 1.2kb constructs. You can do the same, but on the second step use 2x 384mers to get you ~600bp gene. Gibson didn't use DNAWorks to chop up the sequence. He just started from base 1, so that his fragments were F1 [1:60], F2[41:100], F3[81:140], etc.
I think that 15b homology is pretty low (Gibson used 20b for assembling the 60mers in the first step, and 40bp homology for the next assemblies). 60b oligo length is standard.
You can also try one step assembly with all of your oligos (via PCA) as you planned, but I think that the two step assembly might be more efficient.
Let me know if you need more help.
1. Gibson et al, 2009. Chemical synthesis of the mouse mitochondrial genome


text:
How are proteins formed?
Somewhere, I have read that we need to consume proteins to make amino acids to make new proteins. What does it suggest? How do we make proteins from proteins?

I suggest you have a read of the articles on protein and protein metabolism on Wikipedia :) (http://en.wikipedia.org/wiki/Protein_metabolism) This is a really broad topic and it's best if you study it up yourself.

Let me know If I'm right with the phrase "proteins that we consume form new proteins that are different". I'm looking for a simple explanation.

Essentially, yes, "proteins that we consume form new proteins that are different".
The processes are each of them topics for themselves. In short, consumed proteins are digested by peptidases (enzymes) in the stomach, breaking them down into their consituent amino acids. These are absorbed in the gut and transported in the blood to all cells. These take up amino acids and attach them to tRNA molecules which are used in translation to form new body proteins.

Very elegantly worded.

You ingest daily dietary protein which your body hydrolyzes to get all the building blocks for other proteins (amino acids).
Also, from diet you can get essential amino acids that cannot be synthesized de novo by the organism which is more economical than amino acid synthesis. Other amino acids can be constructed by metabolic processes.


text:
TFBS predictions for yeast and pombe?
Are there any resources out there for TFBS (transcription factor binding site) predictions for the yeast (S. cerevisiae) and S. pombe genomes? Even if these are only de novo predictions, I would like to have access to them.

Try YEASTRACT http://www.yeastract.com/

YEASTRACT (Yeast Search for Transcriptional Regulators And Consensus
  Tracking) is a curated repository of more than 48333 regulatory
  associations between transcription factors (TF) and target genes in
  Saccharomyces cerevisiae, based on more than 1200 bibliographic
  references. It also includes the description of 298 specific DNA
  binding sites for more than a hundred characterized TFs.

This question is quite old, but I think it might be useful to mention this:
You can also look at RSAT (Regulatory Sequence Analysis Tools):
go in the Fungi portail, in "motif discovery" choose "oligo-analysis"; there you can predict putative TFBS from upstream sequences for example. It detects repeated motifs. To be more specific of Saccharomyces cerevisiae or S. pombe, select these species in the "Background model" section.


text:
Where can I find a transcriptome of a normal uveal melanocyte?
I am looking for a database where I could find a transcriptome (say obtained with a microarray analysis) of one (or ideally many) normal uveal melanocytes ?

I can't find any transcriptome data, but I did find miRNAome data from GEO at NCBI and Array Express at EMBL.


text:
Can I estimate leaf temperature from air temperature? What other information would be required?
Physiological measurements such as respiration rate and assimilation rate depend on temperature.
Most papers report tissue temperature (e.g. leaf temperature for leaf measurements), although some report air temperature.
My goal is to compare measurements in the literature.  I use leaf temperature at time of measurement to adjust the rates to a common temperature. Currently, I assume that if leaf temperature is not available, it is the same as air temperature. (This is often assumed in papers where the leaf temperature was not measured).
Is there a way to estimate the difference between air temperature and leaf temperature? I can get fairly good estimates of other physiological traits (e.g. leaf thickness, albedo, stomatal conductance) as well as climate data (e.g. humidity, soil moisture content).
My model is:

$T_{leaf} = T_a + X + \epsilon$

And I currently assume X = 0 in my calculations
Is there a better way to estimate X?
Under what conditions would X < 0? X > 0?

I am not a plant physiologist but it seems very odd to me that people are just assuming that Tleaf = Ta without proving it. Surely there must be some old reference somewhere...

@nico perhaps because the error of measurement is >= than the error introduced by this assumption (e.g. if the delta-T is ~1-2C the error might be on the order of 10%). If there is a reference, I haven't seen it cited, and this assumption is made ~ 10% of the time - usually in older papers before thermocouples on the leaf surface at the time of measurement were integrated into standard equipment.

surely, but at some point someone must have started to use thermocouples on leaves... and didn't they check the relation of their leaf measures to Ta? I understand that you cannot generalize that to all plants/conditions, but at least knowing whether the initial assumption is correct would be good. Unfortunately, as I said, I cannot help you with that, my test subject do not have the same temperature as the ambient (and if they have something has gone terribly wrong... :D)

Leaf temperature is a function of air temp, water vapor pressure deficit, net radiation, stomatal conductance, and boundary layer conductance, among other things. Most of these change significantly within the course of a day (or more often), and consequently, so will the offset between leaf and air temp. There are some energy balance models that would be appropriate for estimating this offset (which I'll dig up if I get a chance).

One way to do this is to use the "humid operative temperature" equation, or something similar. A variant of this equation, specifically for estimating leaf temperature, is derived using a leaf energy balance equation in chapter 14.1 of the Environmental Biophysics book (cited below).
I'll let you look up the actual equation since I'm not sure how to do math symbols here. But, in addition to air temperature, you will need to know a few pieces of information:

Vapor pressure deficit - calculated from humidity and temperature.
Incoming radiation - Measured, or you could model this using time of day, latitude, etc.
Emissivity of your leaves - you can probably look this up for your species or a similar one.
Windspeed
Characteristic dimension of leaves - measure, or look up a value for your species (Use this with windspeed to calculate boundary layer heat conductance).
Leaf vapor conductance - a combination of stomatal and boundary layer conductance to water vapor. You must know something about where the stomata are on your leaf (both sides or one side), but you can often look this value up for a given species.
A few other constants that are easy to look up.

That's about it - its a somewhat hairy calculation, but if you have standard weather data and a little knowledge of the plants you are estimating the leaf temperature of, it should be manageable.
This equation and other relevant info are in this book:

Campbell, G.S. and Norman, J.M. An Introduction to Environmental Biophysics. Springer Science, 1998