text:
Is there a way to see what representations are currently displayed in PyMOL?
I am using PyMol to visualize .pdb protein structures.
I show/hide representation a lot, and sometimes I get confused with what representations are currently displayed. So I end up with doing a lot of hides (basically trying to hide each representation).
Is there a command which shows me what representations are currently used.
For instance if I have used
show ribbon
show lines
show mesh
hide lines

and than use some sort of showRepresentation
it will return me ribbon, mesh

If you do that via the context menu on the sidebar, there is an option "show as" that will remove the previous representations and only show the new one.

You can use "as" to switch to a particular style (http://pymolwiki.org/index.php/As
):
as cartooon, 11AS and chain a

You can also hide everything, to remove all representations (http://pymolwiki.org/index.php/Hide):
hide every, 11AS and not (n. ca+c+n and resi 5-10)

I'm a fairly expert user of PyMOL and I've never seen an API exposed which will show you what representations are being used. That's not to say that it doesn't exist, there are a variety of undocumented features and commands still.
The problem is it isn't as simple as ribbon,mesh.  Every single atom can be displaying any combination of representations, so as an API call or command, it would have to return the status of every atom in your selection. If the displayed representations are exposed somewhere they're probably in a very low level format like that, and not of use unless you're a programmer.


text:
What is the mechanism of regulation of PER /CRY genes?
I've read multiple descriptions of biological/circadian clocks and they all mention PER, CRY and CLOCK genes. While I kinda get how they are connected, what interests me is how these actually regulate each other. Do these genes encode proteins that once created bind to the DNA and cover the transcription sites for other genes(like PER protein covering the binding site of CRY)?
A lot of diagrams and descriptions of the process are very complex, and I would appreciate a simple answer (if it exists).

Wikipedia gives a very good explanation of this, on the page for the suprachiasmatic nucleus.

For example, in the fruitfly Drosophila, the cellular circadian rhythm
  in neurons is controlled by two interlocked feedback loops.
In the first loop, the bHLH transcription factors clock (CLK) and
  cycle (CYC) drive the transcription of their own repressors period
  (PER) and timeless (TIM). PER and TIM proteins then accumulate in the
  cytoplasm, translocate into the nucleus at night, and turn off their
  own transcription, thereby setting up a 24-hour oscillation of
  transcription and translation. In the second loop, the transcription
  factors vrille (VRI) and Pdp1 are initiated by CLK/CYC. PDP1 acts
  positively on CLK transcription and negatively on VRI. These genes
  encode various transcription factors that trigger expression of other
  proteins. The products of clock and cycle, called CLK and CYC, belong
  to the PAS-containing subfamily of the basic helix-loop-helix (bHLH)
  family of transcription factors, and form a heterodimer. This
  heterodimer (CLK-CYC) initiates the transcription of PER and TIM,
  whose protein products dimerize and then inhibit their own expression
  by disrupting CLK-CYC-mediated transcription. This negative feedback
  mechanism gives a 24-hour rhythm in the expression of the clock genes.
  Many genes are suspected to be linked to circadian control by "E-box
  elements" in their promoters, as CLK-CYC and its homologs bind to
  these elements.
The 24-hr rhythm could be reset by light via the protein cryptochrome
  (CRY), which is involved in the circadian photoreception in
  Drosophila. CRY associates with TIM in a light-dependent manner that
  leads to the destruction of TIM. Without the presence of TIM for
  stabilization, PER is eventually destroyed during the day. As a
  result, the repression of CLK-CYC is reduced and the whole cycle
  reinitiates again. (http://en.wikipedia.org/wiki/Suprachiasmatic_nucleus#Fruitfly)

The suprachiasmatic nucleus (SCN) is a tiny part of our brain residing in the center. It maintains a biological clock through a gene expression cycle in the individual neurons. The mechanism for humans is very similar to the mechanism for fruit flies, as explained above, but to rehash a bit...
In the fruit fly model there are five players: CLK, CYC, PER, TIM, CRY.
CLK and CYC are transcription factors for PER and TIM, and bind to their promoters in order to activate the expression of PER and TIM.
When the expression level of PER and TIM gets very high, the PER and TIM proteins return to the nucleus, and inhibit their own transcription factors (CLK and CYC) through molecular interactions.
The CRY protein is light-sensitive, and so daylight (or artificial light) will cause CRY to destroy the TIM proteins. Without TIM, we no longer get the PER-TIM dimers that inhibit the CLK-CYC transcription factors.
In humans and other mammals it's the same concept, but with slightly different players (e.g., homologous genes).
What's important here is that we have a biological clock on the cellular level. We haven't gone into how this clock is used yet... But, it's my understanding that the SCN uses the information to tell the pineal gland when to produce melatonin.
The melatonin causes us to be drowsy, lowers our body temperatures, and causes us to fall asleep.
You can see another cycle at work here - our body temperature, which rises with wakefulness, and declines with sleep.
This gives a more general answer to how circadian rhythms are used to influence our sleep cycle. Your question was how the genes involved in circadian rhythms regulate each other. The answer is the transcription-translation negative feedback loop described above.
Hope this helps...

Great answer! I didn't know about "e-boxed" genes, that's something to take a look at !

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/

sort: votes


text:
What is the distinction between chemokines, cytokines, interferons and interleukins?
They all seem to describe molecules of similar function and many people seem to use them interchangeably.
Also please include any other similar molecules if I've forgotten any in the list above.

good question!  I'm interested in learning more about chemokines since there appear to be scores of them, many of which must not yet be characterized.

chemokines comes from chemotactic cytokines

Cytokines is the general class of molecules to which chemokines, interferons, interleukins and others belong. Biologists dispute whether something is a hormone or a cytokine, but generally the consensus goes with if it's to do with immunology it's a cytokine or if the resting concentration is in the picomolar range, but that's a very rough distinction.
Chemokines are molecules that drive cellular chemotaxis. That means they make cells move towards a desired place. Generally chemokines refer to immune cells and there's loads and loads of them.
Interleukins are anything which are messenger molecules between immune cells (inter- means between and -leukins means leukocytes/white blood cells). They're typically denoted by IL + number. However the interferon and tumour necrosis families come under interleukins too in most people's opinion. The interferons are a special group that typically inhibit viruses by making cells non-permissible to viral replication. They also do a few other things like activate macrophages or promote Th1 response, which both also interfere with viruses but there is bacterial overlap. The TNF family is a bit weirder as some are interleukin-like but others aren't as much. TNF-alpha (the classic one) is involved in macrophage maturation. However not all interleukins are strictly between white blood cells, as IL1 acts on the hypothalamus among other leukocytes.
See the problem is everything is a bit grey because most cytokines (if not all) have more than one role and there's never consensus in the world of immunology when it comes to cytokines because more and more keeps getting discovered.

Sounds like immunology in general is just a massive misnomer.

Loads of things in biology were named before they were fully understood. For example haemophilus influenzae doesn't cause influenza - they thought it did before they realised it was a virus. Or the proteins involved in clotting are named numerically 1 through to 12 I think, but don't actually work in order. The immune system has evolved so much from the animal models we use that what we see isn't what we get in the human.

I think 'Junk DNA' is probably a great example of a misnomer ;) but that discussion belongs to chat I suppose XD

In short, this is my understanding following my immunology course (which is mostly identical to AndroidPenguin's answer):

Chemokines: Produce cell movement, i.e. act as chemoattractants. Typically these are used to recruit more immune cells to a site of infection. (Name origin says it all: "chemotactic cytokine = chemokine...)
Cytokines: Produce an inflammatory response by altering transcription (via surface receptor signal cascades). These often act on non-immune cells.

Interferons: A type of cytokine. Secreted by virtually every cell in response to being infected by a virus. Produce an 'anti-viral' state in other cells, through MANY mechanisms. Causes the typical flu-like symptoms.
Tumor necrosis factors (specifically TNF alpha): A type of cytokine. Prepares endothelium (blood vessel walls) to support an inflammatory response by vasodilation, increased adhesion and increased permeability.

Interleukins: Some are chemokines (e.g. secreted by macrophages and dendritic cells upon activation to recruit further phagocytes and adaptive immune cells), others are cytokines (e.g. activating B cells to differentiate into plasma and memory cells after T cell contact).

It should  be noted that not all interleukins yet have a clear function or have an immune-cell source. Also, not all interleukins have an immune-cell target. However, all the ones I know have at least an immune-cell source or an immune-cell target, if not both. Also note that  categories are not mutually exclusive—an interleukin may also be a chemokine, an interferon, or another category not mentioned here like a lymphokine or a monokine.

Pharmacology cross reference: Recombinant type I interferons are injected as therapeutics. Viral infections would seem like logical indications, but interferons are both expensive and have considerable adverse effects, e. g., flu-like symptoms on injection, anemia and depression. Their application is therefore limited to life-threatening viral diseases, e. g. hepatitis C.

Hi welcome to BioStackexchange. Your answer does not exactly address question. Please read the question again and try to improve your answer. Keep contributing !

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


text:
Using DTNP to find free thiol groups on a protein
I've been tasked with using DTNB to find the number of thiol groups on a molecule of Bovine Serum albumin (BSA).
After measuring the absorbance, finding the concentration of TNB and calculating the concentration of the BSA, I've come out with a result of around 0.4 free thiol groups per molecule of BSA, which seems unlikely! There is either a free group or there isn't!
Yet, the implication from the demonstrator is that is is the correct result!
How can this be? Is it possible to get a value of less than one in an experiment like this?

This is a perfectly reasonable result. Remember that you are measuring an average value for a very large population of BSA molecules. Essentially what the 0.4 means is that at any one time, about 40% of the BSA molecules have a free thiol, while the rest of the cysteine residues are disulfide-bonded.


text:
Why do I see an inverted image of an object when I close my eyes?
If I stare at an object for a long time and close my eyes, at first I can still see the object with my eyes closed. But the image I see with my eyes closed is inverted: dark colors appear as light and light colors appear as dark. Why is that?

I think it is because of light adaptation. The rods that are perceiving strong light, downregulate their response. But when the light is suddenly withdrawn then the rods that are adapted to perceive bright light cannot immediately sense dim light.
There are two forms of adaptation- fast and slow. The fast one is Ca²⁺ dependent- decrease in Ca causes cGMP to increase which in turn depolarizes the cell. Calcium modulates this process by other means also. This article suggests that slow adpatation is  because of an allosteric binding of cGMP on transducin-phosphodiesterase complex, which stabilizes this transition state and delays the signaling.
Adaptation can also happen because of photobleaching of rhodopsin.
I don't know how an image "remains" in the eye for a while. I believe it is because of asymmetric slow light adaptation between different spatially distributed rods(some rods take a while to readapt to dim conditions).
Similar effect you can feel with colour vision also. You keep staring at green for a while, then when you see something else it appears reddish.


text:
Why do many fruit trees have five-petaled flowers?
Peach, pear, apple, cherry, and many other fruit trees seem to have flowers comprised of five petals. Assuming there is no evolutionary advantage to confusing students of trees, is there a plausible reason (evolutionary or otherwise) the morphology is so regimented? Are the trees related? Do they like the same pollinators?
Thanks for any insight.

Peach, apricot, plum, pear, apple, cherry trees are plants of the same family, Rosaceae, so they are closely related. They share many more aspects than the five petals. In fact, other plants in this family, and even many other dicots have five petal, simply because their share a common ancestry.

But common ancestry still does not solve the problem: Why 5 ? and not 2 or 3 or even 4 ? Why optimized for Rosales Order at 5, and Brassicaceae for 4 and Numerous for many others ? A number game for sure- but any thoughts on the Advantages these numbers confer? Better reproductive adaptations ?-if then how n why ?

@BBM: The answer might also be that "it just happens to be like this". Not every trait of an organism confers an advantage, and much less is "optimized". You could be interested in reading: http://evolution.berkeley.edu/evolibrary/misconceptions_faq.php#b8

@BBM: early flowering plants had indeterminate petal numbers. The general trend has been towards fewer petals, with fixed numbers. The specific number probably isn't important. However, having a consistent number within a species might confer an advantage in terms of developing a stable relationship with pollinators. Having a consistent number of petals, along with consistent colouring, would enable more controlled & targeted advertising.

It is hard finding answers to this question, which also interests me a lot. The most satisfying answer I have found is detailed in this paper http://www.ijpam.eu/contents/2012-78-3/6/6.pdf.
From the abstract : "This article examines why many flowers are five-petaled through the use of a five-petal model that draws insight from the location of cell clusters at a shoot apex, rather than from concepts such as the Fibonacci sequence or the Golden ratio which have been referred to in the past. The conclusions drawn are that flowers are most likely to be five-petaled, followed by six-petaled flowers, and that four petals are unstable and almost no flower can be seven-petaled."
As for the alternative theory alluded to at the end of this abstract, you may want to check out the work of mathematician Michael S. Schneider (Master's Degree in Mathematics Education from University of Florida). His answer revolves around this idea where, much like what Plato proposed, geometry is seen as the fundamental building block of the universe and where geometric patterns (therefore numbers) are given different meanings based on observational data. In this theory the number five is seen as the "flag of life" if you will. Look-up an image of a DNA strand viewed along axis, I find it interesting that it's mostly in series of five.
That being said, the article I linked certaintly contains a more satisfying answer to your question.
Hope this helped.

If possible add in the main conclusions of the paper you referenced, helps just in case the link doesn't work in the future

This was a in interesting and entertaining article, thank you. It is true that many more flowers than those mentioned in the first answer or my question have 5 petals.

I just edited my answer to include the main conclusions. Also, I would like to put an emphasis here on the following quote from the paper : 'I do not deny the Fibonacci sequence theory in every aspect, but it does not sufficiently explain why a flower is five-petaled.'
I think it could very well be that both the fibonacci sequence theory (in nearly all flowers, the number of petals is a Fibonacci number) AND this new theory can co-exist in a way.
Anyways, glad this helped.

An asymetrical number of petals might offer an advantage: when wind blows there is a clear direction of rotation. Thus the flower turns in one direction only. There is less oscillation that could damage the flower.

This is sort of ingenious. You should be able to test it. +1 for the suggestion.

I cannot explain the downvote. People like to see a reference but sometimes someone has a testable hypothesis with no evidence either way. I think that's worth something.

Didn't downvote, but the fact that this is completely hypothetical with no references probably contributes.


text:
How is gene expression estimated?
I'm reading this fantastic article on estimating body time: Molecular-timetable methods for detection of body
time and rhythm disorders from single-time-point
genome-wide expression profiles and one of the things that is not very clear to me is how the researchers estimated which genes are expressed and which ones are not:

Total RNA was prepared by using Trizol reagent (GIBCOBRL). cDNA
  synthesis and cRNA labeling reactions were performed as described (5).
  Affymetrix high- density oligonucleotide arrays (Murine Genome Array
  U74A, Version 1.0, measuring 9,977 independent transcripts) were
  hybridized, stained, and washed according to the Technical Manual
  (Affymetrix). Affymetrix software was used to deter- mine the average
  difference (AD) between perfectly matched probes and
  single-base-pair-mismatched probes. The AD of each probe was then
  scaled globally so that the total AD of each microarray was equal. The
  resulting AD values reflect the abundance of a given mRNA relative to
  the total RNA popu- lation and were used in all subsequent analyses

I'm not sure if I'm reading this correctly - did the researchers look at all RNA available in the cells and calculated the levels of messenger RNA produced by expressed genes? if not, how can the level of expression of a gene be estimated?

The technique described here is called microarray. Your question has given me an opportunity to put forth one of my opinions about certain problems of gene expression studies.
Gene expression is a measure of the activity of any gene. If the gene performs its activity in the form of a protein, then its expression should be a measure of the protein. If a gene makes a non-coding RNA then its expression is a measure of the RNA concentration.
[You can omit the cases of post-translational modification because of signal transduction. They are highly expressed and transiently but frequently used. ]
Like your example there are many studies which use mRNA concentration as a proxy for protein activity. This proxy works in many cases because transcriptional gene regulation is more frequently used mechanism for imparting stable changes. But the best strategy would always be to measure the proteins also.
Apart from microarray there are several techniques to measure RNA concentration:

RNA sequencing (high throughput)
Real-Time PCR (medium throughput)
Northern Blotting (Low throughput, semi-quantitative)

Many techniques exist for measuring proteins also:

Mass spectrometry (high throughput)
ELISA (Low throughput, quantitative)
Western blotting (Low throughput, semi-quantitative)

Usually the "proxy method" is used because protein quantification is comparatively more difficult. Antibody based techniques like ELISA and Western blotting have problems of cross comparison of proteins because of the variability of the antibody binding efficiency.

when you want to focus on just one gene, qPCR should work better. Microarrays are best for total transcriptome evaluation.

yeah.. one or countable number of genes..

Unfortunately I don't remember the details but I recently saw a talk in a conference where it was demonstrated that mRNA levels don't really correlate with protein levels. I mean, we've always kind of known this but the numbers shown were shocking (less than 50%, perhaps as low as 30). I will try and get a hold of a reference and post back.

Wow, just found an article from 1998 stating that in yeast "We found that the correlation between mRNA and protein levels was insufficient to predict protein expression levels from quantitative mRNA data." And yet here we are, still using such data...

@terdon It varies dependent upon case, for many cases there is a relationship, but its hard to say apriori.  This is difficult if you have a large number of probe sets of interest.    As a rule of thumb, qPCR panels go up to a couple of score of genes or so and then they become difficult.

@shigeta I know, I just have this graph from the conference I mentioned in my head (cannot find it) where the did a transcriptome level analysis and the correlation was pathetic. I'll find it somewhere it was a keystone meeting in Heidelberg can't be that hard to find.

It's my understanding that scientists often use these microarray experiments as high-throughput screening methods to identify either candidate genes or gene networks. If the data from one such experiment is truly to be trusted, it must always be followed up by traditional biochemical methods (mass  spec, western blot, ELISA/RIA, microscopy).

@terdon.. it is not always necessary but there are several evidences that protein levels dont correlate with mRNA levels..

@leonardo: hey mass spec is not that traditional :P

@terdon i've also seen other graphs too -a notable one would have been a graph with many points in George Church's class at HMS I saw once.  Given the state of things, a reference and a reading of the work would be useful.  My recollection was that the correlation was esp at poor mRNA concentrations and that the overall slope was 3 for humans.  Overall correlation wasn't great but it wasn't 0 either.  As always, anyone who expects a solid rule in biology for such things is looking to be disappointed ...

Ok I found and wrote up some of the information around my back and forth with @terdon.  hope some find it relevant.

@WYSIWYG: no, I guess not, but it is certainly quantitative and highly sensitive, so I'm (lazily) throwing it in with the more traditional methods. ;)

@leonardo: you are very right, nowadays that the microarray fad is gone not many journals would accept a study showing ONLY microarray data, without any further validation. Of course, the solution is to jump on the current fad, RNAseq :D

@leonardo: Can you clarify what you mean by MS being highly sensitive? It's my understanding that one problem with MS that you only get reliable (any) readouts for the most abundant of proteins in your sample, no?

@SteveLianoglou: MS is not my expertise, but that is not my understanding (this may vary with the type of MS used, e.g., TOF-SIM, GC). Successful identification of proteins via MS is dependent on abundance but also peptide fragment length (read: experimental optimization). MS can theoretically get down to 1 fmol resolution. Check this out for more information: http://lab.rockefeller.edu/chait/pdf/08/08_eriksson_wiley.pdf

@SteveLianoglou: As I understand MS is sensitive in the sense that it can detect minute quantities but the big problem is the data interpretation

Supplementary information from the Comments from the first answer:
I have perhaps found @terdon's reference?  Not sure if this is it, but by measuring transcription events in individual cells, Taniguchi et al. certainly make the case that there is no correlation between protein and mRNA levels.
However microarray data (and most rnaSeq and qPCR experiments) are ensemble measurements; they measure the average mRNA concentration in a sample of millions of cells.  In the aggregate, the paper also says that in the aggregate, the average mRNA correlates to the average protein product concentration.  See this nice writeup in the OmeSpeak blog.
Overall, what is happening microscopically: translation is a somewhat stochastic process in the individual cell and events have to be modeled explicitly.  Biology in the aggregate (averaged case in a cell population) is often what we have to work with; single cell techniques are quite arduous.  (run a protein gel on a single cell!).  I think there is room for both sorts of information when investigating biology; certainly publication of work measured on more than one cell at a time will continue for some time.
All the work cited here is in E coli, but in Eukaryotes one assumes that this is not going to be any simpler.

gene expression noise is also a variable feature.. in some gene networks, the noise is low whereas in others it is high..


text:
What non invasive methods of estimating Body Time are there?
I found this article on estimating body time using molecular timetable of 168 genes. researchers looked at gene expressions and plotted them to 24 hour cosines curve with some pretty spectacular results.
Unfortunately the techniques discussed required sampling of liver cells, which may be invasive. Are there non- invasive methods of estimating body time/ biological clock/ circadian rhythm time?
An example of body time: at 8:00 real time, a mouse may exhibit gene expressions more appropriate for 9:30, so the body time of the mouse is 9:30.

metabolism is controlled by circadian cycle. I think certain metabolites/hormones can be measured from a blood sample.

For circadian rhythm, the gold standard is melatonin secretion (blood or saliva). Also, core body temperature.
see: Circadian temperature and melatonin rhythms, sleep, and neurobehavioral function in humans living on a 20-h day
James K. Wyatt , Angela Ritz-De Cecco , Charles A. Czeisler , Derk-Jan Dijk
American Journal of Physiology - Regulatory, Integrative and Comparative PhysiologyPublished 1 October 1999Vol. 277no. R1152-R1163

Don't forget cortisol/corticosterone!


text:
How do you average Ki values?
It's embarrassing for me to ask this but well such is life. NIMH Psychoactive Drug Screening Program (PDSP) Ki Database is mentioned as the source of the average binding affinity (Ki) values given in Goodman and Gilman but whenever I try to, in some way, confirm that these values are averages obtained from PDSP I get values that are way (up to 10,000 fold) off the values given in Goodman and Gilman. (ps. I am a mathematician too so I know how to take an average, $\bar{x} = \frac{\sum_i^n x_i}{n}$ so you don't need to hold my hand through the calculation with something as simple as the conventional definition of averages) Therefore I have reached the conclusion that I must be doing the calculations wrong. Please show me how to do them correctly. Here's a screenshot of exactly what Goodman and Gilman says that's confusing me:

Oh and yes I am using just the cloned human transporter values not just all the stuff that comes up.

check the units.. may be a μM to nM conversion problem.. verify

Nope, all the units are nM.

it would be better if you can save this page as a document or pdf and put it in dropbox. Or if there is an ebook then please provide the url if it is possible.

The latter would be a breach of copyright and the other I don't quite understand how that would be better.

Sharing the URL: if it is open such as in the books in the NCBI site. Better: so that i dont need to zoom in to see.

Since I asked this question I found out what I was doing wrong in searching for Ki (i.e. I thought the Ki ID was the test ligand and hence I was searching for drugs the wrong way) values but also how, I think Goodman and Gilman got its Ki values.
I think what they did was they searched for the hot ligand that gave the most consistent and numerous Ki values and took the average of the consistent Ki values (with an relative tolerance of ~100% between results). Additionally since I knew the data, as is stated in the page displayed above, was taken 30 June 2009 I was able to eliminate some sources that were probably not available on PDSP at the time. Using this I was able to get consistent averaged Ki values in the vast majority of cases (with like, at most a small handful of exceptions).


text:
BLAST DNA Sequences Reversed
I have been trying to learn some basic DNA sequencing techniques and have been using BLAST as a reference. I thought that I was starting to get it, but then I cam across this:

It looks like it's saying that the match starts at 10835 and ends at a smaller index (10714).
I tried clicking the link to view the full sequence, and I couldn't find the highlighted portion anywhere (not at 10835 or at 10776).
My question is: Where (in NR_046235.1) can I find the highlighted sequence?
And what does it mean to say that the Sbjct starts at 10835 and ends at a lower index?
I can post my query if necessary.
Thanks.

Just to help you with the answers below - there are lots of online tools which allow you to generate the reverse complement of a sequence if you have difficulty  'seeing' this, e.g. http://www.bioinformatics.org/sms/rev_comp.html

@Alan No need for that, a simple console command does the same for you: (tr ACGT TGCA | rev) <<< 'GATTACA'

I like @KonradRudolph 's one-liner better as a direct solution, but also note that many programming languages have libraries for everyday sequence-processing tasks.

Just to flesh out Daniel Standage's answer a bit, remember that a genome is double stranded with one strand being complementary to the other. Genes can be found on either strand, the two are equivalent biologically. However, sequencing projects choose one of the two strands (randomly) and call it the plus (+) strand and then save all sequences with respect to that strand. This means that sometimes the genomic sequence that you download from a database might be the complement of the actual sequence you are looking for.
BLAST and similar algorithms take this into account and will compare your query sequence to both strands. If your query hits the target sequence on the - strand, BLAST will give a a result like what you have obtained, where the start of the HSP is lower than the end. This is because RNA translation (though not DNA transcription) goes in a 5' to 3' direction, on both strands. We therefore "read" genes in that direction. The coordinates are always with respect to the + strand since we always consider DNA in a 5' to 3' direction, this means that its start position will appear to be after its end position. This is better explained using an image:

In the image above, the blue line represents your BLAST hit. It stretches from position 10 to position 40 (with respect to the + strand). However, since it is on the minus strand, BLAST will show it starting at position 40 and ending at position 10.

Note that the query sequence you have provided matches the minus strand of your target sequence. That means not only that the target sequence will be reversed (as you have noted), but it will also be complemented as well. So in the GenBank record, you should not look for the sequence CCGACCGA... starting at position 10835, you should look for the sequence ...TCGGTCGG ending at 10835.
ccgaccga...    minus strand
||||||||
bbɔʇbbɔʇ...    forward strand

The sequence in the GenBank record contains spaces, so that complicates finding your sequence using the browser's "Find" function, but if you use the position indices at the beginning and end of each line of sequence, you will be able to find the reverse complement of the matched sequence reported in the BLAST results.

Thank you for this explanation! I accepted the answer by @terdon because it was slightly more beginner-friendly.


text:
What processes are responsible for focusing on an image only seen by one of the eyes?
When a person is spying from around a corner with only one eye, it's rather easy to ignore the other eye's image, since it's probably much darker, because one usually spies around a corner standing close to a wall.
But if both eyes get equally bright visual input, it takes some effort to try and stay focused on just one of them. What processes in human body allow such action?

Short answer
Image blur on the retina is the most important monocular cue for lens accommodation.
Background
Focussing of an image on the retina is mediated by the lens. Re-shaping of the lens to focus the image on the retina is called accommodation. In general , the main cues for focussing are retinal disparity and blur, and to a lesser extent proximal cues such as looming, motion parallax and overlay of contours.
When looking with two eyes (binocularly) at an object, retinal disparity is by far the most important depth cue for accommodation. The two eyes look at an object from slightly different angles, so they get slightly different views of it. This difference is the disparity (imperfect match) between the two views. The visual system normally fuses these two images into a single perception and converts the disparity between the two images into perception of depth (Source: Indiana university).
When only one eye is available (monocular focussing), use of retinal disparity isn't possible, and retinal blur becomes the most important factor for lens accommodation. When an image is out of focus, its representation on the retina is blurry. By adjusting the shape of the lens the visual system adjusts the image projection to bring it into focus such that blur is minimized (Horwood & Riddell, 2008). Looming (incoming object becomes apparently bigger), motion parallax (objects further away move slower across the field of view) and overlay of contours (objects closer by obscure things further away) also provide monocular cues for accommodation.
Reference
Horwood & Riddell, Vis Res (2008); 48:1613–24


text:
glossary of biotechnological engineering
Similar to A good book for history of biology/biotechnology for lay people
but not for lay people.
Can anyone recommend an advanced dictionary of biotechnological engineering concepts in English (contemporary, not historical)?
There doesn't seem to be anything adequate at my research institution nor even country.  I have been looking for PDF's and e-books since they can be previewed more easily than ISBN #'s, but any suggestions are welcome.

I found this glossary of Biotechnology and Genetic Engineering off Wikipedia, what do you think?
Or The Facts On File
DICTIONARY of
BIOTECHNOLOGY
and
GENETIC
ENGINEERING
What concepts are you necessarily hoping to include? I'm hoping someone actually experienced in this field can advise.


text:
Do marine deep sea life forms exhibit circadian rhythms? If so, what entrains them?
I've been reading a lot about circadian rhythms, when suddenly this question popped into my head: do circadian rhythms exist for deep sea organisms (3000 ft / 1000 meters+)?
For land mammals, the entrainment of circadian rhythms is done through exposure to light (retina or other photosensitive elements), but in the deep ocean there is no light. How are circadian rhythms maintained there - what acts as an entrainment signal? Is it the moon, currents, etc.?

This, IMHO, is an excellent question.

very interesting question. just a pointer: http://en.wikipedia.org/wiki/Diel_vertical_migration#Importance_with_the_biological_pump plankton migrates between 100 and 1000 meters of depth, so there are regular signals communicated downwards

This study (http://www.sciencedirect.com/science/article/pii/S0967063707002002) shows cyclic activity of a deep-sea fish, with tidal currents as entrainment signals.

A research paper that recently came out suggests that deep-sea life does have a circadian rhythm, but it is regulated much differently than it is by us surface dwellers. We see light, we eat and digest, and the suprachiasmatic nucleus in the brain (our "biological" clock) keeps track of it and eventually establishes a rhythm of the circadian variety.
Most living things at the surface have some sort of circadian rhythm - the mechanisms vary, but they are present and can be readily observed.
In the deep sea, the mechanisms are quite different since they can't see any light, but the rhythm is still established. When these animals (squid in the research) eat a certain type of bacteria containing a light organ, the presence of certain proteins within that organ actually trigger a change in the gene transcription responsible for encoding the protein controlling the circadian rhythm. Thus, when the squid eats, it ultimately determines what the rhythm will be. The entrainment itself actually happens by means of the light organs consumed in the bacteria.
As far as where the bacteria ultimately get there bioluminescence, there is still research to be done, although I would presume there is a mixture of downward bacterial migration and chemical generation contributing to this.
Link to the article: http://mbio.asm.org/content/4/2/e00167-13

Do you remember the name of the article or a link?

not off the top of my head, but I will look for it tomorrow

Heath-Heckman, E.A., Peyer, S.M., Whistler, C.A., Apicella, M.A., Goldman, W.E. and McFall-Ngai, M.J., 2013. Bacterial bioluminescence regulates expression of a host cryptochrome gene in the squid-Vibrio symbiosis. MBio, 4(2).


text:
Do lunar rhythms have impact on human biology, if so, how?
I'm approaching this question from the circadian rhythm perspective. A circadian rhythm is a 24 hour cycle. While doing research on deep sea circadian rhythms, I found this abstract which seemed to imply that there are some kinds of lunar rhythms (about a month long cycle). Lunar Rhythms in the Deep Sea: Evidence from the Reproductive Periodicity of Several Marine Invertebrates:

While lunar rhythms are commonly documented in plants and animals
  living in terrestrial and shallow-water environments, deep-sea
  organisms have essentially been overlooked in that respect.

What do the authors mean by the lunar rhythms? The roughly month long menstrual cycle, or are there other ways that the moon actually influences animal/human biology?

The moon doesn't have a direct effect on metabolism. Nor does it affect menstruation (an archaic theory existed which claimed so!!). The lunar effects are due to its gravitational field which is known to affect tides (Spring tides and neap tides).
Even on a daily basis if you might have observed the sea advances into the beach in the night and recedes in the day. This effect is also because of the lunar gravity.
The abstract of the article, that you mentioned, says that moonlight may have some effect on certain organisms; I am highly skeptical about that.
I think it is just the tidal patterns that might affect the behavior of marine/coastal organisms. I am also slightly skeptical about whether the currents produced by lunar gravitation would be deep enough to affect benthic life. In that case even the heating effect of the sun can produce sea currents. Perhaps it can also produce an upward current because of differential heating.

It would be great if you could add links to a few papers on the topic (am sure someone looked at that...)

@nico: i didn't refer any particular paper for this info. I'll look up and add ASAP.


text:
What does "Activation" refer to in the context of the symptoms of Schizophrenia and Schizoaffective Disorder?
In this journal article certain symptoms are called "activation" in nature. I have never come across this term prior to coming across this article, so I would like to know quite simply what does it mean.

This question might be better placed over on [cogsci.SE] , and they could really do with some more questions

The authors use the Positive and Negative Syndrome Scale (PANSS) to assess symptoms.  One of its cluster scores is activation factor.
Summary:
http://en.wikipedia.org/wiki/Positive_and_Negative_Syndrome_Scale
Original publication of the article, which doesn't list activation factors:
http://schizophreniabulletin.oxfordjournals.org/content/13/2/261.long
Marketed currently here:
http://www.mhs.com/product.aspx?gr=cli&id=overview&prod=panss
None of the sources I saw specified what is meant by activation factor, and many didn't even mention it. It's possible that it's the hyperactivity mentioned in the original publication.  Also, it's possible that it's a modified category in the version sold at the last link. Hopefully this is enough information to get you started, if you want to hunt down the details.


text:
Do immortal organisms exist?
Do organisms exist that are able to live indefinitely if they are not killed by external factors?
Under external factors I would consider things like predators and natural disaster but not illness by bacteria for example.

See http://biology.stackexchange.com/questions/6884/why-is-the-hydra-biologically-immortal

the biggest issues for immortality are internal factors - senescence (aging) is a planned death on a cellular and organismal level.  the above referenced question is a pretty good review of answers. Aubrey de Grey is another good google term to understand proposals which may reverse aging.

If you're referring to the elves of Middle Earth, I'm sorry no they do not exist.

I'm not, I was more looking after some bacteria species. Or maybe some sort of tardigrade..

Umm, that was supposed to be a joke...

I find your distinction between internal and external factors a bit arbitrary. What is your motivation for excluding bacterial infections as external cause of death?
You might be interested in what happens in plants. Here is an example, where the plants get cloned and seem to be able to do this for an indefinite amount of time, but they loose their fertility:
http://www.wired.com/wiredscience/2010/08/aspen-immortality/

I think a lot of this answer hinges on the (artificial) choice of how to distinguish what constitutes an "organism" versus a collection of organisms.

Duplicate: see this http://biology.stackexchange.com/questions/6884/why-is-the-hydra-biologically-immortal and http://biology.stackexchange.com/questions/7010/is-there-any-kind-of-immortality-in-plants

@StevenRoose see this book (http://books.google.co.uk/books?id=4wEspn9gUdoC&pg=PA109&lpg=PA109&dq=extrinsic+causes+of+death&source=bl&ots=Cj-gAk94ZC&sig=wfo9x9I614_TyYEyGa6kUaUoZS8&hl=en&sa=X&ei=HTDbUfrIMsfXtAbasYCYDQ&ved=0CEsQ6AEwAw#v=onepage&q=extrinsic%20causes%20of%20death&f=false) page 108. It defines extrinsic and intrinsic causes of death - as someone studying aging and lifespan I can tell you these are standard definitions and bacterial/viral infections are considered extrinsic.

The immortal jellyfish, Turritopsis dohrnii http://en.wikipedia.org/wiki/Turritopsis_dohrnii

The most amazing thing about this is that if you own one of these creatures, than you can call it "My immortal".

hydra vulgaris & stuff i suggest to read "mortality patterns sugest lack of senescence in hydra" Daniel E. Martinez

I now found this Wikipedia article on biological immortality. It's pretty much what I was looking for.
Wikipedia describes the phenomenon as follows:

Biological immortality refers to a stable or decreasing rate of
  mortality from cellular senescence as a function of chronological age.
  Various unicellular and multicellular species may achieve this state
  either throughout their existence or after living long enough. A
  biologically immortal living thing can still die from means other than
  senescence, such as through injury or disease.

It has a list of such organisms as well, consisting of

tardigrades
hydras
turritopsis nutricula, some sort of jellyfish
lobsters*
planarian flatworms

Addendum: This blog post takes a good look into the myth of lobster immortality. It seems to be as much a myth as the result of any substantial observation.

It would be helpful to summarise the content of your links for future readers

Yes. The Bristlecone Pine, Pinus longaeva, is one example. This species boasts the oldest individual living organisms, and also has been convincingly argued by Lanner and Connor (2001) to show no evidence of senescence.
While the Wikipedia page on Biological Immortality (as of June 2013) unfortunately ignores plants, the pages on Negligible Senescence and Longest-lived Organisms list many plant seeds, clonal groups, and individuals.

 Lanner R, Connor KF. 2001. Does bristlecone pine senesce? Experimental Gerontology 36: 675–685.

This is indeed a correct answer, as many organisms listed on other answers show some aging. The entire list of (presently 7) organisms, including P. longaeva, which do not show signs of senescence is given in a subsection of the reference AnAge database, which collects information on aging of every species: http://genomics.senescence.info/species/nonaging.php

The immortal jellyfish (Turritopsis dohrnii) is capable of biological immortality.

It's one of few known species capable of reverting completely to a sexually immature, colonial polyp stage after having reached sexual maturity as a solitary (free-floating) individual (called a medusa).

Theoretically, this process can go on indefinitely, effectively rendering the jellyfish biologically immortal

 Image source: Piraino et. al. 1996

Citations
Piraino, Stefano, et al. 1996. "Reversing the life cycle: medusae transforming into polyps and cell transdifferentiation in Turritopsis nutricula (Cnidaria, Hydrozoa)." The Biological Bulletin 190(3): 302-312.

Examples found in plant world also- especially those with high vegetative reproduction and regeneration property.
https://en.wikipedia.org/wiki/The_Great_Banyan

Great banyan tree in Indian botanic garden

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
What is the use of futile reaction cycling such as Fruc-P to Fruc-BP?
One rate-limiting step of glycolysis is the conversion of Fructose-6-Phosphate (Fruc-6-P) to Fructose-1,6-Bisphosphate (Fruc-1,6-BP), catalysed by Phosphofructokinase 1 (PFK 1). The reaction involves hydrolysing one ATP to ADP.
The reverse reaction of gluconeogenesis is catalysed by Fructose-Bisphosphatase (FBP). This reaction uses 1 H2O for hydrolysis and yields 1 phosphate (Pi).
One would expect the cell to be utilising only one of the two reactions at any one time, either to break down glucose or to generate it. However, the case is commonly that both reactions are taking place simultaneously in an equilibrium [ref 'Biochemistry', Voet & Voet, 4th ed., 628-629 (Section 17-4-F-f,g,h,(i))], cycling Fruc-1,6-BP to no apparent benefit, at the expense of valuable ATP.
What is the purpose of such futile cycles?

I'd like to note that I have known the reason before, and I'm almost certain I have it somewhere in my material from last year - I just realised that I couldn't explain it to someone right now and I believe this question would be a valuable addition to our site. I am currently busy, but will answer it myself once I am free (unless someone else does beforehand).

gluconeogenesis is not continuously happening and is tightly regulated at the step of FBP. Therefore there is no continuous futile cycle

PFK is not rate-limiting, this has been shown many time. It can't be since it is regulated.

In some organisms such as bubble bees, futile cyclying in muscle is thought to generate heat in flight muscles. Also a futile cycled system can act as a flux amplifier.

This question, like many others on metabolism, is meaningless in referring to "the cell" without specifying what cell one is talking about because the poster does not understand that different animal tissues have different metabolism which is different again from bacteria. Unsupported as it is by any references it should have been clarified when it was asked. Let's just bury it now.

As evident below, the question is perfectly clear and answerable within reasonable scope without specifying which cell type in which species at which developmental time point performs (seemingly) futile metabolic cycling. If there is a meta discussion relevant to this close request, please point me there. "Unclear" is not a valid reason for a close here imo.

As far as I am aware there are various regulatory mechanisms (allosteric regulation, hormonal control) in place to minimise futile cycling by ensuring that phosphofructokinase (glycolysis) and fructose 1,6 bisphosphatase (gluconeogenesis) are not both active at the same time.
See this Wikipedia article for a starting point.

The precise regulation of PFK1 prevents glycolysis and gluconeogenesis from occurring simultaneously. However, there is substrate cycling between F6P and F-1,6-BP. Fructose-1,6-bisphosphatase (FBPase) catalyzes the hydrolysis of F-1,6-BP back to F6P, the reverse reaction catalyzed by PFK1. There is a small amount of FBPase activity during glycolysis and some PFK1 activity during gluconeogenesis. This cycle allows for the amplification of metabolic signals as well as the generation of heat by ATP hydrolysis.

The last two sentences of the quotation are probably what you remember reading about. There is a theory that having some cycling provides an element of regulatory responsiveness. See here for example. I'm not enough of a mathematician to explain this idea well.

You don't need math to understand it. Let's assume the cycling rate is 100 but the net flux is 10. If I increase the forward cycle rate by 10% then the net rate increases 100% (assuming the back rate doesn't absorb all your increase). This is actually a well known effect and was first described in the 1970s by Newsholme.

Phosphofructokinase 1 (PFK 1) is not rate-limiting, its flux control coefficient when measured is invariably small. The fact that textbooks keep suggesting the PFK is rate-limting is just a textbook myth.
Here is a selection of papers that support the observation that the flux control coefficient for PFK is invariably small. There are also very strong theoretical arguments that are consistent with these observations.

Heinisch J. Isolation and characterisation of the two structural genes coding for phosphofructokinase in yeast. Mol Gen Genet. 1986;202:75–82.
Schaaff I, Heinisch J, Zimmermann FK. Overproduction of glycolytic enzymes in yeast. Yeast. 1989;5(4):285–290.
Davies SE, Brindle KM. Effects of overexpression of phosphofructokinase on glycolysis in the yeast Saccharomyces cerevisiae. Biochemistry. 1992;31(19):4729–4735.
Burrell MM, Mooney PJ, Blundy M, Carter D, Wilson F, Green J, et al. Genetic manipulation of 6-phosphofructokinase in potato tubers. Planta. 1994;194:95—–101.
Thomas S, Mooney PJ, Burrell MM, et al. Metabolic control analysis of glycolysis in tuber tissue of potato (Solanum tuberosum): explanation for the low control coefficient of phosphofructokinase over respiratory flux. Biochemical Journal. 1997;322(1):119–127.
Ruijter G, Panneman H, Visser J. Overexpression of phosphofructokinase and pyruvate kinase in citric acid-producing Aspergillus niger. Biochimica et Biophysica Acta (BBA)-General Subjects. 1997;1334(2):317–326.
Muller S, Zimmermann FK, Boles E. Mutant studies of phosphofructo-2-kinases do not reveal an essential role of fructose-2, 6-bisphosphate in the regulation of carbon fluxes in yeast cells. Microbiology. 1997;143(9):3055–3061.
Urbano AM, Gillham H, Groner Y, Brindle KM. Effects of overexpression of the liver subunit of 6- phosphofructo-1-kinase on the metabolism of a cultured mammalian cell line. Biochemical Journal. 2000;352(3):921–927.
Marın-Hernandez A, Rodrıguez-Enrıquez S, Vital-Gonzalez PA, Flores-Rodrıguez FL, Macıas-Silva M, Sosa-Garrocho M, et al. Determining and understanding the control of glycolysis in fast-growth tumor cells. FEBS Journal. 2006;273(9):1975–1988.
Moreno-Sanchez R, Marın-Hernandez A, Saavedra E, Pardo JP, Ralph SJ, Rodrıguez-Enrıquez S. Who controls the ATP supply in cancer cells? Biochemistry lessons to understand cancer energy metabolism. The international journal of biochemistry & cell biology. 2014;50:10–23.

You may be right, but how can we tell unless you cite evidence in support of your argument? Please read the help on how to answer questions properly. Until you elaborate I have voted your answer down.

You're right, I just updated the comment with citation support.

Ok, I've reversed my vote. Unfortunately biochemical metabolism isn't the strong suit of many people on this list and it's difficult to revive interest in an old question. But I look forward to your participation when new questions come up, after the summer perhaps.

I'll try an monitor this forum.

Thanks for making me aware of this, very interesting to find out this idea is backwards. The question wasn't specific to glycolysis though - unless this is actually the only such cycle. The answer I ticked still remains the most accurate answer.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
Amount of reverse transcriptase in µg or mM for qRT-PCR
I am trying to calculate a titration amount for a molecule which I would like to use in my PCR samples. Different molecules have different densities so I would like to calculate the appropriate density of the titrated molecule. How many micrograms or microMolars of reverse transcriptase are used in qRT_PCR kits?

enzymes are generally measured in units

Reverse transcriptase (and most other commercial enzymes these days) is made recombinantly, then purified to varying degrees, using varying methods, among different suppliers (and sometimes between different lots from the same supplier). Some enzymes actually have multiple functional units combined in a complex, others may require a post-translation activation step like phosphorylation by a separate kinase in order to be fully functional. All of these variables can yield preparations of different molar concentration, but very similar activity. Therefore, companies like New England Biolabs have unit definitions for their various products based on activity.
Having dealt with NEB in the past, I know that they generally have a concentration for their products as well, so if you're doing experiments like an enzyme inhibition assay, you can dose for concentration as well as activity. It will vary from enzyme to enzyme whether your inhibitor will even bind to any inactive protein that may be present, in which case activity would be the better attribute to use in your calculations.


text:
Why would low complexity regions be linked with relaxed selection?
I'm reading a text (Wagner, 2007) on identifying positive selection. In the paper, the author says that low complexity regions are known to be associated with the relaxed selection. I'm trying to understand why this is true. I get that if the region is under relaxed selection then most mutations would be tolerated but why would that lead to low complexity (other than something like slippage during DNA replication)
It's in the section: "Little overlap between variation clusters and low complexity regions"
Wagner A. 2007. Rapid Detection of Positive Selection in Genes and Genomes Through Variation Clusters. Genetics 176(4): 2451–2463.

can you provide a link to the text that you are reading so that the context of the author is clear

What is complexity?
"Complexity" in this case is derived from the SEG algorithm, which is based on Shannon's information entropy.
This is not necessarily repeated regions, but regions in which a limited pool of characters are used (for example transmembrane regions, in which you are far more likely to see a hydrophobic residue than a polar one).
These scripts can help you calculate sequence complexity if you have specific examples in mind.
This idea asks how "compressible" is the information in the string of characters (think zip files).
Random characters in strings need more information, whereas less variable, more predictable regions can be recorded with less information and are less complex.
So a region in which you can more easily guess the next amino acid is simple, and more random amino acid sequences are complex. Sequences with more complexity are often more functionally important and more useful as functional indicators than low complexity sequences.
Indeed, BLAST used to mask low complexity regions as they were not useful for homology searches.
Why are complex regions more variable?
The question as I understand it is asking about this fourth conclusion from the paper.

Fourth, variation clusters occur in structurally well-defined and functionally important protein domains of high sequence complexity.

This is now not as paradoxical as it seems. Regions that are highly variable with lots more random/unpredictable amino acids such as those with well-defined structures and functions are more likely to occur in areas with high complexity as a result (which is a measure of randomness in a sequence).
There is more to this than meets the eye...
This is of course not the whole story.
In regions of high complexity, there are highly conserved and essential for life residues that cannot be changed.
On the other end of the scale, there are also areas like STRs that have low complexity yet are highly variable in length between individuals and underpin DNA fingerprinting.

Low complexity regions have repeats in nucleotides ( or amino acids ).  E.g.  PPCDPPPPPKDKKKKDDGPP or AAATAAAAAAAATAAAAAAT.  This 2011 article compares 14 individual Plasmodium falciparum genomes and finds that these repeats are highly variable between individuals - some may be short AAAATAAAA  others may be longer AAAATAAAAAAAAATAAAAAAATAAAATAAAA....AATAA even to scores of bases.
I think its not clear what these sequences do, but the mere fact that they can vary so much from one viable individual to another indicates that they are not strongly selective.  *If they were subject to selection, you would be able to see the difference in the variation in the health, fitness, and reproduction that these significant genetic changes have, but in this case the change in sequence would not change the properties of the sequence much if at all. *
I think these are also related to copy number variable (CNV) regions.  which expand and contract in the genome easily even between identical twins.  (sorry for the indirect reference - like many SDN stories, the reference is totally wrong), but I remember this work...


text:
How many species did Carl Linnaeus classify?
How many species did Carl Linnaeus (senior) classify?

Welcome to biology SE.  I think that while it is answerable, this is a rather narrowly defined question.  You might get a number, but why is this number interesting to you? Is there a larger question you are interested in?

@dd3, I am interested in taxonomy in general, but I'm also curious about this specific question.

More than 13,000.
Plants: >9,000 names.
In Systema Naturae 10th edition, commonly taken as the starting point of modern taxonomy, Linnaeus is reported to have published around 6,000 plant names (I haven't counted, but Müller-Wille gives 5,900 and Stearn says "almost 6,000". The Wikipedia figure of 7,700 may come from a different edition of Systema Naturae).
However, that's just SN10. Luckily, a wonderful source has compiled the names from all of Linnaeus's work:
The Linnaean Plant Name Typification Project of the Natural History Museum says that Linnaeus published more than 9,000 valid plant names in his life (names that are still valid under current nomenclatural conventions), and they have many of them in a searchable database with references to where Linnaeus published them.
Animals: >4,200 names.
For SN10, different authors give 4,236 or 4,378 animal names. Stearn says "nearly 4,400", so perhaps he too was unsure. The total number Linnaues described in his life is probably higher, as he did write separate zoological publications like Fauna Svevica, but I couldn't find a source like the project bringing together all of his animal names.

 Müller-Wille S. 2006. Linnaeus' herbarium cabinet: a piece of furniture and its function. Endeavour 30: 60–64.
Stearn WT. 1959. The Background of Linnaeus's Contributions to the Nomenclature and Methods of Systematic Biology.)

SN10 is the (official) starting point only for zoological taxonomy. In botany Species Planatrum (1753) is accepted as the beginning instead.

Indeed this is a bit of interesting history.  Linnaeus was not a modest man, but he was also a prodigious contributor to biology.  He made many editions of his two major works Species Plantarum (1753) and Systema Naturae published in 1759.  Systema Naturae covered both plants and animals and had 12 editions, eventually with 3 volumes in several parts.
Linnaeus' sampling of species was not broad - he traveled to Lapland France, and England.  His main experience was in botany and was able to look at samples in gardens which were a popular pursuit amongst wealthy hobbyists of the day and visited botanists in England and had samples from other continents.  He had heard about chimpanzees, but it doesn't seem as if he ever saw one.
Wikipedia gives a final count of nearly 10,000 species including over 7000 plants, from the entries in his works.  Linnaeus felt that there would be very few more to be discovered; he estimated 10,000 species of plants which turned out to be completely wrong.  The Encyclopedia of Life has 1,316,775 entries today.  This was probably perpetuated by the influence of Aristotelian thought, which persisted through Darwin's life, that species were only the result a higher reality creating animals attuned to a local climate and geography and so the same species would in the mountains of Scandinavia would be the same as the alpine regions of India say.  But even Aristotelianism, which stood  for over a millenium the 19th Century and Darwin's work, was probably more the result of confirmation bias than any real proof.

Thanks for the detailed answer.  However, you may not know, but Amazing Discoveries is actually a Christian site that makes dubious arguments about evolution elsewhere.  See e.g. http://amazingdiscoveries.org/C-deception-Creation_evolution_theory_compromise

@MatthewFlaschen whoops I guess I could use a different reference - it was unintentional.  I added the wikipedia reference.  I decided to keep the amazing discoveries link because in fairness, the page is pretty fair and credit is due for their good homework.

What's your source for Linnaeus thinking there would be only 10,000 species? Wikipedia (quoting Stearn) says 10,000 plant species. For comparison, EOL lists 250,000-380,000 plant entries.

Quite right - I changed my response.  I think the point still holds that Linneaus had no idea how diverse the biological world was, or really how species worked.

Complete agreement!

One comment on the dates for Systema Naturae: the first edition was published actually in 1935, while the first volume of the 10th edition (which is taken as the starting point for animal taxonomy) was issued in 1758.


text:
Example(s) of reduced rate of mitotic progression?
Most species complete mitosis, and in particular the process of chromosome condensation, rather quickly, in a matter of minutes. Are there any known species that undergo mitoses with substantially reduced kinetics (on the time scale of hours), particularly with respect to the processes of chromosome condensation (prophase through metaphase) or decondensation (anaphase through telophase)?

don't know about mitosis but oocytes are locked in metphase for several years.. the second round of meiosis (gametogenesis) begins only at puberty.


text:
Resource plant anatomy/lifecycle vocabulary
I've been curious about a lot of vocabulary words in the world of botany. I've had quite a bit  of trouble finding somewhere online to help me out, but I'm having some trouble finding a resource like that.
Optimally, I'm looking for something with diagrams of anatomy, over the course of time, maybe some photo examples, and some sort of dictionary to accompany. Is there anything like this, online or offline that anyone knows about?

Re-reading your question, I realize my answers below may be too general. Are you looking for a resource specifically about ontogeny, for example seed>seedling>adult anatomy?

I mostly wanted to know what parts of the plant are being affected by different things. For example, I have some apple seedlings that had a problem up to the ridge where the cotyledon stopped and the rest of the plant started, is there a name for that, if so, what is it?

I imagine there are resources targeted specifically to growers, and that the folks in the Gardening SE would be better positioned to tell you about them. However, I've also added one more resource to my answer below that may help.

I find that the folks at Gardening SE are incredibly knowledgeable, but aren't exactly botanists... I like both sides and was curious what to ask perhaps a botany professor. Thank you for your answer! I think that book looks good.

specifically development-focused
An Introduction to Plant Structure and Development by Beck looks comprehensive and has been well-reviewed. It has both photos and diagrams, and sections certainly deal specifically with growth/lifecycle. It's available to preview or purchase as an ebook on Google Play.
more general plant anatomy vocabulary resources
In print, Plant Identification Terminology: an illustrated glossary by Harris and Harris is a fairly standard reference, and I've found it very useful both for looking up terms and for just flipping through.
Online, but with fewer diagrams, you could try the Glossary page on the Angiosperm Phylogeny Website.
This might sound silly, but if you're looking for more of a course on the fundamentals rather than a dictionary of the specifics, the Botany Coloring Book is actually a great, seriously useful work.


text:
How does MEME compute the background frequency of nucleotides?
I am trying to calculate a log-odds matrix for MAST input, from a position-specific probability matrix for the motif in which I am interested.
I would like to know how MEME estimates the background frequency of nucleotides, as it does the conversion from position-specific probability matrices to log-odds matrices when you choose to run MAST on MEME output.  Is it simply counting frequencies in the sequences supplied, or is there some sort of modeling going on to correct for sample size and whatnot?
EDIT: Another possibility that occurred to me is that MAST is capable of converting position-specific matrices to log-odds matrices.  I'd appreciate it if someone could clarify this point for me (and I'm still interested in how the background frequencies are calculated).  Also, I am specifically looking for answers with links to supporting documentation.
EDIT 2 (05/07/13): Alexander has answered the original question.  Does anyone have an answer to the first edit (re: MAST)?
EDIT 3: MAST doesn't like PSPMs; it will accept the job but crash.

I am not sure about the exact algorithm but the wikipedia page on MEME, briefly explains the algorithm and how the weights are computed. You can refer to the original paper; they must have explained it in the supplementary info.

At the MEME server page, there's a link to upload a customized background markov model (using the command line interface, this is the -bfile option).  From there, there's a link to the MEME Man Page.  Under "Objective Function", it specifies:

The background model is an n-order Markov model. By default, it is a 0-order model consisting of the frequencies of the letters in the training set.

So yes, it's basically the simplest possible correction: no accounting for pairwise frequencies, complements, motif width, etc.  I expect this is because MEME can be applied to essentially any dataset, such as phage display bindings from a "truly" random set of short oligos. In which case making higher order assumptions about the pairwise independence would be detrimental.
Below that, I think it answers your question about the total log-odds calculation:

The E-value reported by MEME is actually an approximation of the E-value of the log likelihood ratio. (An approximation is used because it is far more efficient to compute.) The approximation is based on the fact that the log likelihood ratio of a motif is the sum of the log likelihood ratios of each column of the motif. Instead of computing the statistical significance of this sum (its p-value), MEME computes the p-value of each column and then computes the significance of their product. Although not identical to the significance of the log likelihood ratio, this easier to compute objective function works very similarly in practice.

Thank you for the clarification re: MEME. Do you know if MAST also does the same computation? I know it works with log-odds matrices, but I am interested in whether it also can accept position-specific matrices.

In the couple of instances that I've used MEME, I found it sorely lacking in documentation. It seemed to make the assumption that the user was already pretty expertly trained in the field. My impression is that it should be able to handle a pretty sophisticated Markov model, but I don't know how you would construct it. I tend to work at the opposite end of the comp bio spectrum. :)


text:
can the face of a person be accurately predicted from DNA information?
http://blogs.smithsonianmag.com/artscience/2013/05/creepy-or-cool-portraits-derived-from-the-dna-in-hair-and-gum-found-in-public-places/?utm_source=plus.google.com&utm_medium=socialmedia&utm_campaign=20130503&utm_content=collageartdna
Can the face of a person be accurately rendered just from analysing a DNA sample of that individual?

I posed a similar question a while back. You might want to check it out, even if the answer is inconclusive...

Not accurately. Assuming the DNA information is the DNA sequence, you can't tell which genes are being expressed and which are being silenced. These are through chemical groups on the DNA which aren't generally picked up.
Also there's the environment that grossly affects what you look like, how much you weigh, your skin colour and cosmetic surgery.

Just for added clarity, the chemical modifications I referred to were epigenetic mechanisms of methylation and histone acetylation etc.

Just saying grossly means net-gain. It's used when describing things like financial matters, and really doesn't make sense here..unless you mean they've had some sort of terrible accident :P

@Starkers in medical terms it means that which is visible to the naked eye. It also is used for financial matters. It's a homonym.

@Starkers Gross Anatomy... It's probably not a bad idea to assume someone knows something you don't until you can prove them incorrect.

It depends what you mean by "predict". Consider that the faces on genetically identical individuals, such as identical twins, are very similar, even in old age. If you look at the processes of development over the life of an individual as a more-or-less deterministic and predictable phenomenon, then you might argue that faces are predictable from DNA info. The fact that no one has ever done this from first principles is another issue - in principle it is possible.

So you are saying it is possible to analyze someone's DNA and determine approximately what their face will look like?

I'm saying that if "nature" can reliably produce similar-looking faces from similar DNA, then there is an underlying mechanism operating which is accessible to scientific investigation, possibly leading to a technology of predicting facial features by examining a person's genome. But not yet.

That's cool. It would/will be interesting to see what comes of that in the coming years. Thank you for sharing :)


text:
The effects of dust particles
When sun rays shoot through my house from a window, sometimes if the lighting is correct, it will reveal a huge amount of floating particles and dust.
Are these particles dangerous to humans if you live with them constantly?

You asked the single most difficult questions ever, so be proud of yourself! I've spent some time in the lab with a post doctorate trying to answer that particular question. It all is based on something called the hygiene hypothesis: the belief that as we are getting cleaner we are seeing less and less bacteria and so our immune system isn't working as it should so we get allergies. There's lot to this theory with regards to the different white blood cells in our body (specifically Th1, Th2 if you've ever heard of them). Of course there are reverse hypotheses, because we avoid eating stuff like peanuts, but minute amounts is found in dust, dust exposure (which also contains bacteria) makes us think peanuts are harmful so that's why we have allergies.
Realistically a bit of dust to the most of us isn't harmful but if it contains things like dust mite poop which many people are allergic to, cat skin (another seriously common allergy) or is leaking from a place with mould... you should be okay :)

It's not just a bit of dust though... there is so much everywhere when the sun reveals it. It looks unhealthy....

I wonder if there's an optical component to this as well. If I cross my eyes the right way, I can see dust particles in bright light too...

Our basic defenses such as nasal hairs and mucus help in trapping the dust particles and other Suspended Particulate Matters (such as smoke etc).
However, if there is too much of dust inhalation then, as you suspect, it will be harmful. This can be seen in quarry workers who inhale a lot of dust- which causes silicosis.
Dust also instigates asthma.
You would feel much more comfortable in a dust free greenery but the mild dust which you would notice in your house wont be very hazardous in usual circumstances.


text:
qrt-pcr and short fragments
I plan to measure the effects of Tenofovir a Nucleotide analog reverse-transcriptase inhibitors useing qrt-pcr with HIV-RT as the rt enzyme. Tenofovir causes early termination of the reverse transcriptase by binding to reads preventing the continuation of the chain process rather than stopping the action all together. How will qrt-pcr quantify the low molecular weight short incomplete fragments? I think since the areas complementary to the forward and reverse primers will rarely be on the same continuous double stranded dna expression will be decreased uniformly. Is this correct? Will I need to use absolute qrt-pcr since the changes will be the same for all genes?

You have to design your primers properly. Usually, in real-time PCR, you don't choose a very long product. Ideal product size is 150-300.
Next, see what your NRTI is analogous to. For e.g. if I am using AZT (Azathymidie), I would place my reverse primer at or after the last T.
There are alternate techniques as well. You can use primer extension (radiolabeled) and then quantify different products by scanning the photograph. However, this technique won't be as  quantitative as real-time PCR.


text:
I'd like to know the name and a few details of a certain time-keeping structure in the human brain
I once heard of this structure on the Discovery Science channel and have since forgotten the name. The details I remember about it were that it is the central time-keeping device for the brain located in the geographic center of the human brain. The DSC only mentioned it in passing to describe a person with an abnormality in this structure. Can someone post some reliable research links and a short description of it? I don't trust google much and am not good at using it, so thanks!

You are probably referring to the suprachiasmatic nucleus.
Note that, although this is the central clock, there are also so-called "peripheral clocks", for instance in the liver, pituitary and other organs that can finely tune rhythms in the organism.
You may also want to have a look at the Wikipedia page for circadian clock and references therein.

okay thank you very much, that looks like what i was referring to. I also heard it was very very small, and the wikipedia article said 20k neurons and the size of a grain of rice. I'll remember circadian clock too!

Suprachiasmatic Nucleus is a part of Hypothalamus, which might be an interesting read as well - hypothalamus is very important


text:
Detecting Introns and Exons
I know that when RNA is transcribed from the original strand of DNA it contains introns and exons, and that the introns are spliced out of the strand to provide genetic diversity. However, what I don't understand is, how does whatever is doing this splicing know whether the section it is reading is an intron or an exon? Are there start and stop codes like there are for polypeptides, or is it determined by epigenetic factors like methyl markers? Or is it neither?

Quick answer: we don't really know.
As WYSIWYG said, splice sites do have a sequence signature. The image below (taken from [1]) shows the consensus for human acceptor and donor sites:

In the images above, the size of a nucleotide represents its frequency at that location. As you can see, there is a clear signal around the splice sites and this signal is used by various programs that do splice site prediction. What is not quite clear yet is how the cell recognizes these signals. Sometimes a "perfect" (identical to the consensus) splice site is ignored by the cell in preference to one that we would consider "worse". This is further complicated by the presence of various downstream and upstream signals such as splicing enhancers, silencers and structural elements (loops, hairpins etc) in the mRNA molecule.
So, to answer your question yes there are start/end markers for introns/exons but they are far more complex than the simple START and STOP codons of transcription. We know know a lot about it but we still don't fully understand the details of splicing.

References
Brent MR, Guigó R., Recent advances in gene structure prediction, Curr Opin Struct Biol. 2004 Jun;14(3):264-72.

There are some signature sequence which mark intron-exon boundaries. Usually introns start with a GU and end with an AG. But this feature per-se is not sufficient for splicing; there are other cis-elements such as exon/intron splicing enhancers/silencers [ESE/ESS; ISE/ISS]. Refer this article.
Also, there are protein regulators of splicing such as SR proteins; other proteins such as Fox-1/2 can control alternate splicing events.


text:
Histidine aromaticity
I understand that the imidazole ring in histidine is aromatic. I also realize that it retains its aromaticity when protonated.
I am wondering why this is not mentioned at all in basic text books such as Lehninger? Also, across the web there are a number of places claiming that histidine isn't aromatic in all cases.
Another reason I am a little confused is, if protonation doesn't alter the aromatic nature, then why is histidine such a weak base?

This is one of my favorite charts demonstrating the complexity of amino acid properties:

http://www.jalview.org/help/html/misc/aaproperties.html
Histidine is probably the most complicated amino acid in this regard (just compare how many circles it falls into).  But don't undersell cysteine and methionine: those sulfurs exhibit some surprising behavior, especially when coordinated properly.  Cysteine, of course, forms disulfide bonds, with methionine occasionally functioning as a methyltransferase.
Biochemistry textbooks make some oversimplifications because presenting the full messiness of these classifications is pretty confusing. Lehninger is the worst about this, especially when presenting math.  Voet and Voet is probably the most reliable about presenting this complexity. I still think Lehninger is a better teaching textbook overall (I was first taught biochemistry from the 3rd edition), but I also recall spending a week being confused about a topic before someone pointed me at V and V and I realized Lehninger was oversimplified to the point of being wrong, in that case.

Diagram is nice and informative +1 :)

@Dexter I also like the diagram. Do you agree these are improvements? 1. "Tiny", rather than "tiny". 2. Instead of blue, green, and grey as the main colors and blue (twice, which is confusing) and brown (which is so dark as to make reading the black print difficult) that are hard to distinguish, howabout the big three being the light primaries ie red, green, and blue? Then the overlaps would be more clear (and have intrinsic interest). 3. How about distinguishing medium/big/huge? As it is leucine and tryptophan are lumped together. 4. Removing the "Charged" ellipse, since it adds nothing.

Contd. 5. How about representing size by position, e.g. distance from the center of the "SMALL" oval, or from the center of the diagram as a whole? That way, the ranking by size could be made clear, and even the actual magnitudes of the size. 6. How about something more precise than "small" and "tiny". Does it refer to volume, mass, number of atoms, or something else?

I am wondering why it is not mentioned at all in basic text books such as Lehninger?

Books are not flawless.

Another reason I am a little confused is, if protonation doesn't harm the aromatic nature, then why is histidine such a weak base?

Pyrroles have a weak basicity because of delocalization of the electron lone pair of nitrogen. It is the lone pair of nitrogen, in amines, which gives it basicity (Check Lewis bases and acids) .
In imidazole, the other nitrogen (N-2) has a free lone pair and does contribute to its basicity. As you pointed out before, imidazolium is a stable moiety and imidazole is a much stronger base than pyridine, although it is a weaker (pKb ≃ 7) base than lysine (pKb ≃ 10.5) and arginine (pKb ≃ 12.48).
Imines are generally weaker bases than amines because the sp2 hybridization of the former gives them a more s-like  character; this causes the lone pair to be held more tightly to the nucleus thereby reducing the basicity. Also, the C-N(2)-C angle is constrained (small) because of the planar ring. This again leads to a more s-like character.
The strong basicity of arginine is because of the guanidium group.

The imidazole ring in histidine is indeed aromatic. But "aromatic amino acid" does not usually mean "amino acid with an aromatic ring". Rather, it indicates one or more particular chemical properties, such as high absorption at 280nm, or, better, its metabolic pathway.
Histidine as a stand-alone amino acid is a weak base, but this is mainly due to the amino group and acid group that every amino acid has. The imidazole ring itself has a neutral pKa.

I was referring to the basicity of the side chain itself. Why is its pKa neutral?

i dont think there is a term called neutral pKa.
pKa of water is ~15.7. pKa of imidazole is ~14 which makes it slightly better acid compared to water but poorer acid compared to carboxylic acids.

@WYSIWYG: I was referring to the deprotonation of the acid conjugate, physiologically more relevant. pKa≃7. I agree that 'neutral pKa' is a misnomer.

The reason why it's mostly referred to as basic is because the non-protonated nitrogen in the ring has a lone pair that it actively donates in several biochemical reactions. Lone pair donator = Lewis base

Hi and welcome to Bio.SE! This is more of a comment on the protonation rather than the aromaticity. Once you get more reputation you'll be able to make comments. If you want to expand your answer, see these tips on writing a good answer.

Consider it as an amino acid with "pro-chiral auxiliary" properties instead of broadening the entire molecule as aromatic.

Welcome to SE Biology. You may not have noticed that this badly confused question was posted almost ten years ago, and the poster has not been on the site in the last eight. If you think that the description "pro-chiral auxiliary" is an important general contribution to the topic, then you need to explain what it means. I am a native English speaker, have a degree in Chemistry, and have taught biochemistry for many years. The phrase means nothing to me.


text:
Why is herpes virus neurotropic?
A neurotropic virus is a virus which capable of infecting nerve cells.
Herpes simplex virus (HSV) has low neuroinvasivesess and high neurovirulence. HSV is transmitted in vesicle fluid, saliva and vaginal secretions. So the site of infection determines the disease - "mixing and matching of mucous membranes".
Source: Murray 2013, Medical Microbiology.
Why is herpes virus neurotropic?

What's the difference between neurovirulence and neurovasiveness

1/How Herpes does it:
Quote: << HSV... can enter the Peripheral Nervous System by binding to receptors on axon termini of sensory and autonomic neurons, which respectively convey sensory and visceral information. Most alpha herpesviruses use this route to enter the PNS and establish a life-long persistent infection [3].
Human alpha herpesviruses include herpes simplex type-1 (HSV-1), HSV-2. Well-studied animal alpha herpesviruses include pseudorabies virus (PRV) and bovine herpes virus (BHV). The cellular adhesion molecule, Nectin-1, is a major neuronal receptor for these viruses. Alpha herpesvirus particles enter sensory nerve endings by membrane fusion, and engage dynein motors for retrograde transport to the neuronal cell body or soma [4]. The capsids then dock at the nuclear pore and the viral DNA is instilled in the nucleus where an acute or a quiescent, latent infection is established. These viruses are unique in maintaining quiescent infections in the PNS neurons of their hosts. This quiescent state can be reversed by certain stress stimuli, which results in the production of large numbers of progeny in a relatively short period of time (1–2 days) [5]. Despite the direct synaptic connection of PNS neurons to the CNS, spread of alpha herpesvirus infection to the CNS is rare, but debilitating, in natural hosts [3]. Alpha herpesvirus trafficking, latency and reactivation is further reviewed in the following sections. Quite complex paper that outlines the nerve invasion strategies of majore nervous system virii, even rabies, polio, smallpox: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3647473/ >> end quote
2/Why Herpes has a particular advantage:
HSV has a statistically efficient infection and dormancy habit(near 100% of adults, 60% of them have HSV-1) It has the particular ability to achieve suspended animation, blocking the nerve immune response with special RNA strands, even if is detected there, inside nerves, it stays very benign/docile, it can stay latent in a host for very many years...
The last thing a virus needs is a dead end host, it's main objective is to spread and maintan as widespread a host population as it can. When we’re healthy, HSV-1 snoozes inside our neurons, secluded from drugs and the immune system. the latency is controlled by dissemination RNA strands that control the host nerve cells ability at apoptosis, or programmed cell death due to infection, so it can live as a reservoir of virii inside a cell for many years.
Herpesviruses have been infecting and codiverging with their vertebrate hosts for hundreds of millions of years. The primate simplex viruses exemplify this pattern of virus-host codivergence, at a minimum, as far back as the most recent common ancestor of New World monkeys, Old World monkeys, and apes. Humans are the only primate species known to be infected with two distinct herpes simplex viruses: HSV-1 and HSV-2. https://www.ncbi.nlm.nih.gov/pubmed/24916030
Red blood cells and other cells don't live as long as nerve cells: Most neurons are formed before birth and survive for the lifetime of the individual, so their lifespan is the same as that of the body. (for peripheral nervous cells the figure is also impressive, they can even grow back when damaged).
When it breaks out, it has an efficient vector of transmission which more controlled and less alarming than smallpox or more virulent virii, and enable the hosts to stay associated with is group during and outbreak, rather than causing the host to become an outcast. Animals instinctively take fright of pathogen symptoms and can distance themselves from shared foods, objects, and periphery of a symptomatic host. Herpes only causes very minor symptoms.
The transfer of viral particles between individuals, as the production of viral particles does not necessarily require any noticeable damage to the host.
HSV achieves this using a very fine tuned balance of latency or lyse/cell outbreak, which is when it explodes host cells and causes an immune response that sheds the virii at the surface.
The RNA latency control mechanism is highly evolved and fine tuned to control the nerve cell, there has been recent research about it, it's here: https://en.wikipedia.org/wiki/HHV_Latency_Associated_Transcript
this means that nearly 100% of the adult population is infected with the herpesviridae family of virii: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3809354/
Other virii have different survival strategies, like cold and flue virii, which flee to the epithelial cells of the host in order to not decimate the host population, as if to flee the host by going to the surface of the host, because they don't have much control over their own virulence in through other methods, they don't know if they are being virulent or not.
...
Other than that, HSV automatically explodes epithelial cells, and it's ability to enter and hide inside nerve cells is it's strength. it's very complex how it does that, HSV is a very adapted, sleek, efficient virus.
I can't prove this theory, but it's possible that this HSV can confer added robustness to the host population, by keeping it's nerve immune response tip-top through the generations, and make it more able to combat other nerve virii like H1N1. Sometimes it's difficult to think that a virus that has been with use for millions of years is not part of of the body itself.

Simply because it has neurotropic receptors. Why did acquiring these receptors seem evolutionarily advantageous? Well the immune system doesn't target nerve cells for destruction as well. There are few if any white blood cells in the CSF within which the neurones are bathed. The immune system is about protecting against damage, it doesn't care as much if a virus doesn't cause damage as it isn't geared to respond as well if that's the case.

Excellent answer and clear logic! I like it!


text:
What is meant by "alien" probe in a microarray?
In my lab we did a microarray to analyze differential gene expression in S. cerevisiae treated with UV irradiation. We are now analyzing the results and one of the up-regulated genes is labeled "Alien4_60." I believe this is some kind of control, but I am having trouble understanding what it is.
I would think that a probe labeled "alien" in a microarray would be some kind of negative control. The probe-list (excel file) says "Control stringency: 60% identity to oligo Alien4" as the description for this probe. What does this mean?
..As you can imagine, searches for "Alien4" only brings up sci-fi movies!
p.s. perhaps someone with enough rep could tag this question with more meaningful tags.

It's a probe to detect external 'Alien' RNA standard, a synthetic mRNA commercialized by Stratagene/Agilent.

The Alien RNA transcript is a ~500-nt, polyadenylated RNA molecule that
  is synthesized by in vitro transcription. The Alien RNA transcript is
  nonhomologous to all known nucleic acid sequences currently in public
  databases, as determined by BLAST comparisons against NIH sequence
  databases. https://www.chem.agilent.com/Library/usermanuals/Public/300602.pdf

As any other external standard, you spike in the same amount of Alien RNA standard in your different reactions and then using the Alien probe you can normalize for extraction efficiencies etc. It works not only for microarrays, but also for qPCR, RNA-seq etc.
If you didn't spike in any of it, I expect your probes giving very low signal that's probably why you thought about negative controls.


text:
Are any organisms known to use meiosis I to create non-identical offspring asexually?
So, there are numerous species of animals who use parthenogenesis, but to my knowledge the reproduction is clonal. That is, the offspring are identical to the mother. Are there any documented cases where a female goes through meiosis one to produce varied cells that are now diploid and these cells do not go through meiosis two, but rather develop in to a diploid organism? It would seem an effective reproductive strategy in that it generates genetic variation without a mate (at least more-so than strict asexual reproduction). Is my logic flawed in some way?

In automixy the meiotic cells give rise to diploid offsprings. This can happen by diploidization of the haploid cell (1n->2n), which will produce homozygotes or endomitosis prior to meiosis (4n->2n) which produces heterozygotes. Examples:

Cnemidophorus uniparens : 4n->2n
Sphyrna tiburo: 1n->2n

I don't know of any case where there is fusion of similar gametes to form a diploid cell. It is difficult for two ova to fuse in natural conditions because the vitelline membrane has to be dissolved.
Experimentally a haploid ES-cell can be fused to ovum to form a progeny. Haploid ES cells undergo diploidization and when injected in blastocyst, can develop properly (Ref). In fact haploid androgenic-ES cell line had been made in this study by injecting sperm into an enucleated oocyte. These androgenic-haploid cell lines can be fused to ovum to give rise to viable offsprings.
Also see this question. Similar topic

Good to know! However, I was under the impression that Cnemidophorus lizards gave rise to clones. If I understand you (and the article) then this gives rise to varied offspring. Obviously there is no infusion of new genetic information from other individuals, but it would still seem farm more advantageous (especially in vertebrates) to produce offspring in this way, than by a mitotic mechanism. I find it odd that there don't seem to versions of automixy (that I can discern) that simply forgo meiosis II. Wouldn't this be the simplest way to generate variation and maintain chromosome number?

It is indeed surprising.. Usually the metphase-II spindle starts assembling before meiosis-I ends.. Slight delay in this process can cause nucleus to assemble¹ ² ³ and perhaps the dihaploid cell can convert to diploid.


text:
Why does blood come from mouth when people are shot in the chest area?
In almost every movie scene when a character is shot in the chest area, some blood comes from his mouth or sometimes even coughs blood before he dies.
Are these kind of scenes realistic/possible? If yes, why does blood come from mouth in this situation?

Its mostly Hollywood. It can happen but it's a stretch. Like a car blowing up. The myth busters blew that one out of the water and they could probably do the same her. It's possible and can be explained, but not probable.

Substances such as blood trigger the Cough reflex, so if for any reason blood accumulates in the airways, it will be ejected this way.
If you have a look at chest anatomy, you can see how this could be caused (look at Trachea down to the lungs, aorta and the carotid arteries above the heart). A shot through the chest can peforate many large blood vessels, along with the airways, and cause leakage inside.
I would consider it quite hard to hit the aiways like that though, the bullet would have to enter the chest quite near the centre as the cough reflex is not triggered by substances in the lung itself, only in the airways. There may be other ways of blood getting into the airways, but I would assume that a scene with a shot near the breast and then blood coughing would be unrealistic.

Image source: Micheau, A (2010) ANATOMY OF THE MEDIASTINUM: ILLUSTRATIONS AND CROSS-SECTIONS. From: http://www.imaios.com/en/e-Anatomy/Thorax-Abdomen-Pelvis/Mediastinum-Illustrations

Nice answer, +1. Could you include a link to where you got the image from please?

Here you go, there's many more nice pictures where that came from :)


text:
What is the name of the baboons that live in Saudi Arabia
In Saudi Arabia there are a lot of baboons in the mountain area. I would like to know what's the name of this specific baboons so I can read about them more:

These look like Hamadryas Baboons (Papio hamadryas). They also fit the geographical location.


text:
How can I clean phenol extracted RNA?
I extracted RNA from skin and quantified it in an Nanodrop machine. The 260/230 ratio was very low and two peaks appeared in the absorbance curve, but the RNA is ressuspended in RNAse free water. How can I clean it?

wash it with chloroform..

Phenol absorbs at 230 nm, this is the most likely contamination in your case. You should try to avoid pipetting from the phenol phase, or use a phase lock gel to make this easier. I assume you washed it a few times with pure chloroform after the phenol/chloroform mixture, that should help to get rid of the phenol.
I only precipitate my RNA with 1-1.5 volumes of isopropanol after the chloroform/phenol extraction, that should be sufficient for most uses. Just add the isopropanol, keep it at -20°C for 30 minutes and then centrifugate it at 9000 g for 20 minutes, redissolve the pellet in water.