text:
Is it possible to grow a fertilized human egg entirely outside the woman's womb?
Many science-fiction movies (for example, The Island) show the possibility of growing a fertilized human egg cell (from the beginning to the end) outside the womb of the woman.
This means that you have to create the exact circumstances for the fertilized egg cell to develop into a human being. These exact circumstances coincide, obviously, with the womb of a woman.
Doesn't this require a woman, where those circumstances are exact, which means the only place where a fertilized egg cell can grow is the woman itself? So basically I'm saying that you need a woman (the womb is connected to the entire body) to let the single fertilized egg cell into a fully grown 9 months baby.
Well, this isn't exactly true: after development for 5 months or so in the womb, an artificial environment can take over, which is possible with current technology. But to devolop the fertilized egg right from the start is another story? Can it be done, or is it impossible (of which I'm certain, but nevertheless I ask this question)?

I believe what you're describing is referred to as ectogenesis which is essentially developing a fertilized egg inside an artificial womb until it’s able to survive outside the controlled environment. So is this possible outside of science fiction? To answer this we have to compare the stages of human reproduction and how close today's science and technology can come replicating/sustaining them.
We'll begin by dividing these stages into two groups: fertilization and development of embryo to fetus.
When it comes to answering the question of whether fertilization can be replicated in vitro or not, the answer is yes it can be done! In fact in vitro artificial fertilization (IVF) has been possible for several decades. In most cases when IVF is performed the egg is then placed inside the mother's uterus where it goes onto to develop into an embryo and then fetus. In regards to "ectogenesis" the IVF egg would be placed into an artificial womb.
In order to form a zygote (fertilized egg) to develop properly into a fetus it has to be an environment to meet it needs. In a female uterus all these needs are met but replicating them might be difficult. An artificial womb would have to be able to provide nutrients, oxygen, and channels for the development process of a fetus as well as system to expel (birth) the fetus once its development is complete. So can today's technology and science do all this? In theory yes, if resources and time where dedicated (and red tape cut) it would be possible to develop a fertilized egg in an artificial environment within the foreseeable future. There have been multiple experiment where artificial wombs were implanted with fertilized eggs and began to grow but were stopped due to legality.
I encourage you to read the following Wikipedia and motherboard articles regarding artificial wombs and ectogenesis.
https://en.wikipedia.org/wiki/Artificial_uterus
http://motherboard.vice.com/read/artificial-wombs-are-coming-and-the-controversys-already-here
*Note there is a lot of biology I did not mention regarding zygote to fetus development which is the biggest question/obstacle that ectogenesis might face

Thanks for your answer! But to make the fertilized egg grow the right way don´t the egg´s circumstances must be an exact copy of the womb, wich can only develop in the woman (and thus out of a fertilized egg cell). So don´t you need for the development of the fertilized egg something that can only spring from a fertilized egg wich developed in the womb? I can´t see how the development of a human fertilized eggshell, considering the growth from one cell to the fully grown baby, is compatible with an artificial womb made out of the conscious thoughts and hands (-made mechanics) by men. :-)

Okay, getting the egg to grow is not the problem, getting the egg to grow correctly would require trial and error. As far was matching the condition of the uterus, I "feel" would not be impossible, the reason I say this is discussion the uterus its self is very simple, it is composed of smooth muscle lined with glands . You can look at an experiment done at Cornell where a mouse was grown inside an artifical uterus to see its impossible, the cell grew but the mouse was severly deform and ultimately died before being "born".

But it´s not only the uterus that´s involved in the growth of the just fertilized egg. Also, the woman that surrounds the egg, and even more affects the growth, and that´s something we can´t imitate.

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text:
What do sharks not like the smell of?
I was reading about the sharks strong sense of smell ( Shark senses - @EnhancedLearning.com ) and wondered if any research has been done into what they don't like the smell of?
Is there any material that they don't like being near and would stay away from?

Could you provide a link to what you were reading?

Shark senses-@EnhancedLearning.com . Maybe they could mix a deterent into surfboard wax or wetsuits (:

I don't think one can easily determine what smell sharks don't like. You know, you can't easily find whether a shark turned around from something because it didn't like its smell or it wasn't interested in it, especially tiger sharks ;)

@another'Homo sapien' , if I could name one I wouldn't need to ask the question? With the advances in biotechnology and other areas in recent decades it is more than possible that we could make something that deters sharks, I think to say it doesn't exist or can't be done is very narrow minded (with all due respect it's figure of speech) .

There could be a marine creature that contains something that makes the sharks not like to eat them or see them as a snack.

@another 'Homo sapien' I was just guessing with the puffer fish I , agree this is going a bit off topic from the O.P, thank for the input anyway (:

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text:
Can one talk about deacetylation of a promoter rather than associated histone?
I am confused on a detail in a paper I am reading and am not sure whether I am misunderstanding the wording or misunderstanding the concept.  I am including the whole abstract of this paper for background:

Epigenetic regulation of uterine biology by transcription factor KLF11 via posttranslational histone deacetylation of cytochrome p450 metabolic enzymes.
Zheng Y, Tabbaa ZM, Khan Z, Schoolmeester JK, El-Nashar S, Famuyide A, Keeney GL, Daftary GS.
Abstract:
Endocrine regulation of uterine biology is critical for embryo
receptivity and human reproduction. Uterine endometrium depends on
extrinsic sex steroid input and hence likely has mechanisms that
enable adaptation to hormonal variation. Emerging evidence suggests
that sex steroid bioavailability in the endometrium is determined by
adjusting their metabolic rate and fate via regulation of cytochrome
(CYP) p450 enzymes. The CYP enzymes are targeted by ubiquitously
expressed Sp/Krüppel-like (Sp/KLF) transcription factors.
Specifically, KLF11 is highly expressed in reproductive tissues,
regulates an array of endocrine/metabolic pathways via epigenetic
histone-based mechanisms and, when aberrantly expressed, is associated
with diabetes and reproductive tract diseases, such as leiomyoma and
endometriosis. Using KLF11 as a model to investigate epigenetic
regulation of endometrial first-pass metabolism, we evaluated the
expression of a comprehensive array of metabolic enzymes in Ishikawa
cells. KLF11 repressed most endometrial CYP enzymes. To characterize
KLF11-recruited epigenetic regulatory mechanisms, we focused on the
estrogen-metabolizing enzyme CYP3A4. KLF11 expression declined in
secretory phase endometrial epithelium associated with increased
CYP3A4 expression. Additionally, KLF11 bound to CYP3A4 promoter GC
elements and thereby repressed promoter, message, protein as well as
enzymatic function. This repression was epigenetically mediated,
because KLF11 colocalized with and recruited the corepressor
SIN3A/histone deacetylase resulting in selective deacetylation of the
CYP3A4 promoter. Repression was reversed by a mutation in KLF11 that
abrogated cofactor recruitment and binding. This repression was also
pharmacologically reversible with an histone deacetylase inhibitor.
Pharmacological alteration of endometrial metabolism could have
long-term translational implications on human reproduction and uterine
disease.
Citation:
Zheng Y, Tabbaa ZM, Khan Z, Schoolmeester JK, El-Nashar S, Famuyide A, et al. Epigenetic regulation of uterine biology by transcription factor KLF11 via posttranslational histone deacetylation of cytochrome p450 metabolic enzymes. Endocrinology. 2014;155:4507–20.

My question is on the fourth-to-last sentence of this abstract specifically:
"This repression was epigenetically mediated, because KLF11 colocalized with and recruited the corepressor SIN3A/histone deacetylase resulting in selective deacetylation of the CYP3A4 promoter."
This sentence seems to say that SIN3A/histone deacetylase is deacetylating the CYP3A4 promoter itself (i.e. it is deacetylating a region of DNA directly).  However, shouldn't a histone deacetylase be deacetylating a histone, not a region of DNA?  Am I misunderstanding the mechanism?  Or is "deacetylation of the CYP3A4 promoter" really a short-hand way of saying "deacetylation of a histone that is associated with the CYP3A4 promoter"?
Thanks in advance for your help!

The promoter sequence is wrapped by histones, which a modified (look at figure 3). "KLF11 binds distinct nuclear cofactor complexes that posttranslationally modify promoter histones to epigenetically alter the chromatin state, gene expression levels, and activity"

Thanks @GerganaVandova.  Just to make sure I am understanding the wording correctly:  is it always ok to refer to a histone modification as a modification of the corresponding gene (as the authors seem to do in the abstract)?  For example, if we were talking about histone methylation, it would be confusing to phrase a statement as "methylation of XYZ123 promoter" (since DNA methylation and histone methylation are two separate phenomena).  Is it acceptable in the case of histone acetylation, since there's no such thing as DNA acetylation (as far as I know)?
Hope this question makes sense!

I would say yes, it is probably acceptable, but I agree that the authors should have been more clear by stating that changing the acetylation state of the histones wrapping the promoter affects the expression of the gene from that promoter.

@Georgana Vandova. I've edited the title of this question, deleted my own comment and turned it into an answer. That way the question can be answered and eventually taken off the unanswered list. As your comment is more extensive you might like to do likewise (and perhaps reconsider your attitude to the acceptability of the statement).

The authors obviously meant to write that the histones associated with the promoter become deacetylated. They cannot mean the promoter itself as that is DNA.
What they wrote is not shorthand or acceptable alternative usage, but just a mistake — published papers often contain typos and mistakes of this sort. Probably the authors meant to write the technically correct form of words but lost a phrase. Or perhaps they had exceeded the limit to the number of words allowed in the summary, and so they went through trimming, but trimmed too much.
Why didn’t the referees pick this up? Of course they should have, but they were probably more concerned with the contents of the paper and whether the experiments described by the authors justified their conclusions. They are busy scientists and probably doing the job voluntarily.
In conclusion, scientists are human, scientific writing is difficult, and everyone makes mistakes. But we should still try to convey our ideas as clearly as possible, and certainly not copy something that is technically incorrect or ambiguous, just because it has made it into print.

This is all about DNA-Protein interactions.
The promoter region of the DNA is interacting with the Histone modifications, which are controlled by other proteins.

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Difference between pulse coupling and diffusive coupling In biological oscillators

What are the differences between pulse coupling found among neuron cells and diffusive coupling found in cells that exhibit calcium waves?
Moreover, in both methods, is it a strict requirement that the cells have to be adjacent to each other or at a distance from each other.

I know this is not a mathematical forum, but can anyone answer the next question or at least point out some books/article where I can learn them.

How can we represent pulse and diffusive coupling mathematically?

I don't know what you are referring to in Q1. What calcium waves? Can you give us a reference?

@Memming Intracellular calcium waves. For example

Partial answer:

As for a book on the topic of mathematical modeling of coupled neural oscillators, you can start with:

Wilson, H. R. (1999) Spikes, Decisions & Actions: Dynamical Foundations of Neuroscience, Oxford University Press, Oxford UK. author's copy, amz


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Online multiple sequence alignment with constraints
This is probably a naive question.
I have accesssed the Clustal Omega online multiple sequence alignment tool at http://www.ebi.ac.uk/Tools/msa/clustalo/ for the first time, but I think I need to provide more input to get it to do what I want, by specifying more constraints.
Edited to clarify constraints:
The original sequence P sequence has four symbols, say A,B,C,D.
The algorithm has access to 4 derived sequences.
P1: all occurrences of A,B deleted, no other change
P2: all occurrences of A,D deleted, no other change
P3: all occurrences of C,D deleted, no other change
P4: all occurrences of B,C deleted, no other change
Goal: given P1,P2,P3,P4, recover P
Example
P:
ABACCADDACBBC
P1
CCDDCC
P2
BCCCBBC
P3
ABAAABB
P4
AAADDA
Note that I have removed the under bars by which I had tried to indicate deleted symbols but since the deletion processes for the Pi are deterministic they can be supplied to Clustal or whichever tool is appropriate.
End of edit
Toy madeup example illustrating my input, the output, and the problem.
The actual sequence from which these sequences came after deletions, followed by the resulting sequences is as below:
p  ABACBAC
p1 A_AC_A_
p2 _BA__AC
p3 __ACBA_
so I input
>p1
AACA
>p2
BAAC
>p3
ACBA

and got the output
p1 _AACA_
p2 BAAC__
p3 __ACBA
      **

Which is entirely reasonable, but I have constraints.
I want to align with the constraints that

for certain symbols matches between certain sequence pairs should be maximized, and
for certain symbols mismatches between certain sequence pairs are allowed

In fact given p1,p2,p3,p4, which all arose from p after deletions, there are the pairwise constraints

A should be a match between p3 and p4 (it never appears in p1 or p2)
B should be a match between p2 and p3 (it never appears in p1 or p4)
C should be a match between p1 and p2 (it never appears in p3 or p4)
D should be a match between p1 and p4 (it never appears in p2 or p3)

This means that p1 has only C,D; p2 has only B,C; p3 has only A,B; and p4 has only A,D characters after deletion.
I want to obtain the most likely alignment or a few most likely alignments of p1,p2,p3,p4 under these constraints.
I have looked to see if I could figure out how to input the constraints but no luck.
Should I have used another tool? In general I will have much longer sequences, typically 4 of them, with pairwise agree/disagree constraints, as stated above.

This question is unclear. What do you mean by A,B, C and D? Are these residues, or points in a list. I think you should expand on your toy sequences.Assuming you can't post your actual sequences, perhaps use another real peptide and make up similar constraints to the ones in your own problem (although I still don't understand what your constraints are).

I also don't understand your constraints. Also, why do you need constraints? Usually when you do MSA, you don't pose any constraints since you presumably don't know how the query sequences can be aligned. Also, I bet that if you include sequence "p" in your MSA, the alignment will be different and will include your constraints.

@James, thanks for your comments, I will re-edit the question to clarify.

@GerganaVandova, thanks, will rephrase the question.

Answer
You can't. Clustal doesn't provide the options of setting the sort of restraints you would like. Multiple Sequence Alignment (MSA) is difficult to program and the authors of Clustal have been refining their algorithm for years. If it were perfect and completely robust they might be in a position to add more user tweaking, but at the moment you're stuck with those provided.
Comparison matrices and forcing alignments
It may be worth while to mention how one can force particular correspondences in simpler pairwise alignments. This involves manipulation of the comparison matrix used to score the comparison. DNA comparison matrices may be very simple, scoring, say, 1 for a perfect AA, TT, GG, CC match and 0 for any mismatch. Protein comparison matrices are more complex, with the values for perfect matches dependent on rarity and unique function (e.g. In the PAM250 substitution matrix WW scores 17, whereas GG scores only 5) and the values for mismatches also varying markedly (e.g. ED scores 4, compared with 5 for EE; but EW scores –7). There are various matrices available, so implementations of the Smith Waterman and Needleman and Wunsch pairwise comparison algorithms generally allow you to specify your own.
Suppose you have biological information (not intrinsic in the algorithm) that makes you wish to force an alignment. For example, AAATAA sequences near the polyA tail of two mRNA 3'UTRs should align, but sometimes do not because other stretches of As give better scores. What you can do is replace the AAATAA by AAAZAA in each case, and then modify the scoring matrix so that ZZ scores very highly (e.g. 20) compared with AA. This will force the alignment, after which you can change the Zs back to Ts.
Multiple Sequence Alignments tend to to use position-specific dynamic scoring matrices. As the overall sequences align, the original scoring system is adjusted to reflect the frequency found at a particular position. (For example if a position is skewed to E in 90% if cases, EE will score more than at a position in which E is found only in 20% of cases).
I'm not saying it would not be possible to change the initial Clustal matrix with Zs at a particular position, but I don't think this possibility is provided. (Anyway your situation is more complex.) Glancing at the Clustal Omega paper, I see that they allow, indeed encourage, you to build up alignments from previous profiles. If you managed to force the alignments of a few sequences and input the profile derived from that, you might get what you want. But I imagine that requires the command-line program from Dublin, rather than the EBI online version.


text:
Significance of upper-case, lower-case and Ns in UCSC DNA files
I have downloaded human chromosome's data from UCSC FTP. Some part is in small alphabets and some is in large alphabets. Does it show the coding and non-coding region?
Here is an example from the file I just downloaded:
gagaatcccttgaacccgggaggcggagcttgctgtgagccgagatcgca
ccactgcactccagcctgggtgacagagccagactccgtctcaaaataaa
taaataaataaataaataaaAAAGAAAAAGGTTAATACAACATTAAAGAA
CAAGAATTAATATAGCtttttttttttttttttttttttgagacctagtc
tcactctgttgcccaggctggagggcagtggcatgatctcagctcactgc
aacctccgcctcccgggttcaggcgattctcctgcctcagcctcccgaat
aggtgggattacaggcgtgcaccaccatgcctactttttgtatttttagt
agagacggggtttcactatgttggccaggctggtgtcgaactcttgacct
caagtgatctgcctgccttggcctcccaaagtgctgggatgacaggtgtg
agccactgcacctggccTAATATAGCTTTAATAGAAAAGGAGCTAATACA
AGCTTAGAATAATAAACTTTATGCAGACTTACTGAAACAAACAGTCAATG
CAACCTTAACCAAACAGGAATTGATAACAGTTTAATAAAAAAGCTAATAC
CACTTGAATAGAATATATCTTACTACAACCTTCATAAGAAAAACAACTAA
TAcactttgggagaccgaggcaggcagatcacgaggtcaggagatcgaga
ccatggtgaaaccccgcctctactaaaaatacaaaaaaattagcctggca

Second strange thing is to see it beginning with sequence like NNNN. Like here it is:
>chrX
NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN
NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN
NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN
NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN
NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN
NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN
ctaaccctaaccctaaccctaaccctaaccctaaccctCTGaaagtggac
ctatcagcaggatgtgggtgggagcagattagagaataaaagcagactgc

So the question is two fold:

What is the difference between upper and lower case in nucleotide fasta sequences?
What are the repeating N characters denoting?

On the web page that you linked to there is a file named README.txt. I suggest that you read it.

@mdperry I did. But it has nothing related to these N's and lower/upper case

"Repeats from RepeatMasker and Tandem Repeats Finder (with period of 12 or less) are shown in lower case; non-repeating sequence is shown in upper case." This is the relevant passage in the README.txt file. As described in one of the answers, in the IUPAC symbol table for referring to nucleotide bases, where the most common ones are ACGT and U (typically in RNA), the 'N' symbol is used to either represent a base in a sequence motif pattern where any of the 4 may be found, OR in a sequencing run, a base position where the actual base could not be unambiguously determined.

The FTP download files are documented on the UCSC site (from which they also may be downloaded from a web browser). The page for the human genome is http://hgdownload.soe.ucsc.edu/goldenPath/hg38/bigZips/. I don't know which files you downloaded, but I quote three of the descriptions:

hg38.2bit - contains the complete human/hg38 genome sequence
      in the 2bit file format.  Repeats from RepeatMasker and Tandem Repeats
      Finder (with period of 12 or less) are shown in lower case; non-repeating
      sequence is shown in upper case.
hg38.fa.gz - "Soft-masked" assembly sequence in one file.
      Repeats from RepeatMasker and Tandem Repeats Finder (with period
      of 12 or less) are shown in lower case; non-repeating sequence is
      shown in upper case.
hg38.fa.masked.gz - "Hard-masked" assembly sequence in one file.
      Repeats are masked by capital Ns; non-repeating sequence is shown in
      upper case.

It would appear that the number of Ns corresponds to the number (perhaps an estimate) of bases the identity of which are not known. This is suggested by the following on the general downloads FAQ page at https://genome.ucsc.edu/FAQ/FAQdownloads.html.

N characters at beginning of human chr22
Question:  "When I download human chr22 from your web site, the
  unzipped file contains only N's."
Response: There is a large block of N's at the beginning and end of
  chr22. Search for an A to bypass the initial group of N's.

Difference between UCSC and GenBank files
If you download the human chromosome data from GenBank you will not find the lower-case characters (i.e. they are not a standard feature). The reason they are in the UCSC files is because these files are the ones used within their Genome Browser, which displays these repeats, as illustrated below.

Lowercase letters indicate repeat-masked regions. N's represent gaps.
See:
https://groups.google.com/a/soe.ucsc.edu/d/msg/genome/S4Sx8UdJAwM/tLTpVVzdhFMJ

How is the number of N's determined ?

In my experience, a run of N's, like 30 or 50, or 100, used to indicate a gap between two mapped contigs, but nowadays, with NGS sequencers I think they usually represent a base that could not be determined unambiguously, and thus for the purposes of length measurement we know the Number of bases in the fragment, but not the actual sequence of every base.

Sequence in caps are usually regions of interest, such as exons. N in the DNA alphabet refers to "unknown nucleotide" It can refer to any of A/T/C/G when the actual underlying base is unknown.

The IUPAC Nomenclature symbol table for RNA and DNA nucleotide sequences (via Wikipedia)


text:
Paired-end illumina sequencing
I'm tying to understand the mechanism of paired end illumina sequencing, however I dont't  understand why index primer 1 and index primer 2 are used.
paired end illumina sequencing (YouTube).

What do you mean with index primer 1 and index primer 2? Do you mean the barcodes? They are necessary to separate your samples after sequencing. Or do you mean the long adapters which are attached to your samples?

That's the problem hahaha, I saw on the video that they are only 3 basepairs long @TheGreenOne

Then you also did not recognize that it was not really scaled as the remaining part should be about 250 bp long for one direction.

Let me begin in the sample preparation to explain you the index primers.... and let me assume please that you want to sequence amplicons like 16S. Let me further assume that you have 96 samples, which means that you have one complete PCR plate full of samples. First you prepare your samples. You are doing a amplicon PCR, clean that PCR, attach the adapters which are necessary that the sequences can bind to the glas slide and at last you are attaching indexes.
You are attaching these barcodes individually for each sample.
Looks like that image:

source: https://www.neb.com/~/media/Catalog/All-Protocols/C411AB12AFB04000BED567FC17B2A4AA/Content/PCRPlate.jpg

Let's call such indices barcodes (index = barcode). As you can see, each sample gets its own combination of a indexing primer as you are using always to primers (i7+i5) for each sample. Whats important is, is that all these primers are individuals like:
Line:
1: AAAAAT
2: AAAATT
3: AAATTT

and:
A: TTTGGG
B: TTGGGG
C: TGGGGG

(In reality these primers are longer and more complex!)

After you have done such a indexing PCR and also cleaned your PCR (get rid of the polymerase, something like this) you have to pool your samples (put them all together) before you are sequencing. And thats the point why such indexes are important. Without indexing you would have no chance to get your samples separated (=demultiplexed) again after sequencing.
When you are sequencing paired-end then you are sequencing one time forward (barcode + adapter + the sequence you want to have) and one time reverse (barcode + adapter + the sequence you want to have). One big amplicon of e.g. 500 bps gives you two sequences: the forward sequence (also called forward read) and the reverse read.
Let's call the forward read: R1
And the reverse read: R2

After sequencing you have one big pool of sequences. What you are doing first is to demultiplex your samples. As you know now you have for each samples hundreds of thousands of sequences: each consists of two Parts: The R1 read and the R2 read. What you are doing now is to separate your sequences again: You know that you used for example the indexing primers AAAATTTT and CCCCGGGG (just examples!) for your first sample. So you know that AAAATTTT belongs to the forward (R1) read and CCCCGGGG belongs to the reverse (R2) read. This means, that, when you separate all sequences which contains at the "barcoding/indexing-position" these sequences, you know that these are sequences which belong to your sample 1. For sample two you used for example the barcodes AATTAATT and CCGGCCGG and then you know again: AATTAATT belongs to the R1 read and CCGGCCGG belongs to the R2 read. Filtering that sequences out and save them in an additional file you will get your sample 2 separated. And that's why such indexes are important and that's also the reason why you always have to indexes: one is used for the forward read, and one for the reverse read.
Additionally: Why basically we have to use primers is the following: If you want to sequence an amplicon you (or at least the machine) is only able to sequence about 250 bps in each direction. When you are attaching indexes (which are in each case needed) then you are able to sequence in both directions: forward and reverse. And afterwards, when you have demultiplexed your samples you can run an assembly to put the forward and reverse reads together again.

great explanation! Thank you so much @TheGreenOne


text:
How can I search for and find specific biology topics in scientific journals?
I looked on google to find "scientific paper on biological explanation of homosexuality" but nothing comes up that appears reliable or from a journal. Then I looked up "scientific journals" and I found a directory for them, and searched through that directory, but of all the journals, I cant seem to find an efficient way to search for topics in these journals over the web.
Is there a way to efficiently search for specific scientific journal papers, specifically for biology?

https://www.ncbi.nlm.nih.gov/pubmed/ is probably the most common way to search for papers in this area of science.

And scholar.google.com is an alternative to pubmed.

Note that the directory you found, OMICS International, is a predatory publisher according to Beall's list; I would be highly suspicious of any journals you find there.

note pubmed restricts itself to reputable journals, google scholar does not. so use google scholar to find terms then switch to pubmed to look for more detailed papers.

There are two possibilities for searching for scientific articles:
The first one is to use PubMed, a database which has been set up by the National Institute of Health in the US. It contains about 25 Million journal articles. All articles in this database are coming from peer-reviewed journals.

The other one is to use Google Scholar, which is better when you are unsure about search terms. It will give you more results, but you have to be careful here, since not all hits are from peer-reviewed journals, sometimes you get some quite questionable sources.

As a general purpose tool for searching the scientific literature (or even biology in general) I would argue that PubMed is poor. Outside medicine the coverage is hit and miss. The main pro is that it's open for all to search.

While the core focus of PubMed is on the medical literature, the nature of medical research means that coverage of the biosciences is extensive, where the discipline can be related to human health. As a consequence much of genetics, molecular biology and biochemistry is also covered. For additional coverage adding more of the agriculture, environmental and ecological domains try EuropePMC (http://europepmc.org/) which adds literature from the ARGICOLA (http://agricola.nal.usda.gov/) database to the PubMed/MEDLINE/PMC data.

@HamishMcWilliam Well, "much of" isn't really good enought for a general purpose search tool for biology. The fact is that "much of" ecology and evolution (areas where I'm most familiar) isn't covered by either PMC or EuropePMC, and the same goes for e.g. taxonomy. For this particular question, the journals Journal of Homosexuality, Evolution and human behavior or Journal of Human Evolution could be relevant, but neither is covered by PMC.

@fileunderwater Interesting to note that the three journals you mention are categorized as focusing on the humanities by JournalSeek. Checking the list of journals included in PubMed (ftp://ftp.ncbi.nih.gov/pubmed/J_Medline.txt), articles from Journal of Homosexuality (e.g. https://www.ncbi.nlm.nih.gov/pubmed/26914706), Evolution and human behavior (e.g. https://www.ncbi.nlm.nih.gov/pubmed/26880866) and Journal of Human Evolution (e.g. https://www.ncbi.nlm.nih.gov/pubmed/26852814) do appear in PubMed, although they appear to be recent additions so only a limited set of articles are present.

Well, that doesn't really say much. And you don't have to look very far for journals not covered by PMC; Evolutionary applications, Animal conservation, Biodiversity & conservation, Method in Ecology & Evolution, Journal of Biogeography... The list goes on and on and on.

Basically, if you think that searching within PMC gives you an overview of what is published in biology, you get a very incomplete and distorted view, as well as a lot of geographic bias. And as you've noted, single papers can sometimes show up, but that is because authors are sometimes required by funders to deposit them there (e.g. many publicly funded american authors, which will increase the geographical bias on top of the underlying journal bias).

@HamishMcWilliam Don't get me wrong, PMC is good for what it is: an open directory where everybody can search. But you have to be aware of its limitations vs e.g. Web of Knowledge or Scopus. PMC is not a broad general-purpose database of Science (or biology). We should probably move this to chat though.

Worth noting that Web of Science, Scopus, SienceDirect, etc. also do not cover all the scientific literature. In my experience they can be missing stuff which is present in PubMed. So if you looking for broad coverage you have to search all the databases you can access, and even then you will likely be missing stuff. Where stuff is publicly available Google Scholar and web searches may help fill gaps.

@fileunderwater From my experience in various topics of biology, Pubmed is not to bad. The rest can be done with Google scholar, that`s why I recommended both.

Web of knowledge (from Thomson-Reuters) and Scopus (from Elsevier) have the broadest coverage of peer-reviewed journals, if you have access to them through your library. Google scholar is a free option that also covers a lot, but with poorer search options and less quality control. Pubmed is an alternative, but coverage in many areas of biology outside of medicine (or other scientific fields) can be poor.

If you have access to library resources with your university, Scopus is brilliant. It allows you to search specific topics and articles published by a particular author.
http://www.scopus.com/

Short answer: use a free literature search service such as PubMed or EuropePMC. As an example of how to use it for the example you give, searching EuropePMC "evolution of homosexuality" (as a phrase) gets you to this paper, the full text of which is then available straight from the search result.

The best way to find scientific papers on a specific topic is to use a literature search engine. There are five main ones I'm familar with so will discuss specifically: PubMed, Google Scholar, Scopus, Web of Science and EuropePMC.
Each has advantages and disadvantages. There are some published comparisons of different search providers (e.g. Falagas et al. 2008, Anders & Evans 2010, Schultz 2007) but the main difference in practice unless you are at a major university is that PubMed, Google Scholar and EuropePMC are all free, while Scopus and WoS are subscription-only.
Other major differences include:

PubMed is designed for biomedical use, although in my experience
coverage of other areas of the life sciences is acceptable. There are
tutorials on using PubMed here.
Google Scholar includes a lot of 'grey literature' which is not
peer-reviewed, which could be an advantage or a disadvantage. I tend
to steer clear of it unless I am specifically interested in the grey
literature.
Scopus and Web of Science (previously Web of Knowledge) are
subscription service operated by Elsevier and Thomson Reuters
respectively. Both integrate additional article metric functionality
for example H-index and impact factor, although it
doesn't sound like you would need these. I find Scopus slightly
easier to use and a few comparative studies suggest its coverage is
slightly more complete but there's not much to choose between them.
Finally, the 'new kid on the block' is EuropePMC which seems to be
very similar to PubMed but apparently indexes substantially more articles
than PubMed. It also has some nifty functionality such as searching
by grants, linking to ORCIDs etc. It allows search automation via
software packages which is very useful for systematic reviews etc
(others may also do this but if so I haven't found it yet). I think it's becoming my favourite.

As a final cautionary note, different search services cover different journals and have different biases. If you're doing a systematic review paper or meta-analysis the official PRISMA guidelines recommend using at least two different services to minimise this problem.
(Many thanks to the many other users who added useful comments and shorter answers to this question; I'm just trying to collect them all together)

Pubmed: you can find articles about medical fields.
Biological sciences (proquest): a very specific database for biological articles.
Web of science: suitable for interdisciplinary articles.


text:
why does the score matrix influence the E value (BLAST)
When I align two HBB protein sequences wich have 80% identity, I used two kind of score matrices: Blosum62 and PAM30, to figure out the impact on my results.
I noticed that the bit score is higher when I used PAM30 instead of BLOSUM62, which makes sense because PAM30 is based on more closely related species.
However I don't understand why the E-values differs from each other:

PAMP62: Bit score: 251, E value: 8 * 10^91
PAM30: Bit score: 258, E value: 6*10^82

Question: I don't understand why the E-value changes when using an other scoring matrix?
thankyou,

Perhaps this BLAST tutorial by Steve Altschul will be helpful:  The Statistics of Sequence Similarity Scores
There is also the BLAST book by Mark Yandell and Ian Korf.

The Altschul article is definitely what you should look at as it's on the BLAST website. There is one relevant section entitled: "The choice of substitution scores" and another entitled "The PAM and BLOSUM amino acid substitution matrices". Have fun digesting them!


text:
How to calculate information content of a DNA sequence
How does one calculate the information content of DNA sequence like ATCGGCT where mutation rate of G's is 10% and the most common mutation product binds with C and A with equal frequency.
I know that the individual information of a sequence is the dot product of the sequence and the weights matrix for each base. Essentially I = sum (base1xweight + base2xweight + ...)
What I can't figure out is how to determine the the weight of each base so as to incorporate the 10% probability of mutation of G's.. Can anyone help me figure that out
EDITED since wording may be confusing:
Original problem says:
" Spontaneous deamination of exocyclic amine is dG (deoxyguanosine) can occur occasionally in DNA strand. Given probability of this occurring  during the time it takes DNA polymerase to copy DNA is 20% per dG in a particular DNA. Given that most common deamination product pairs with dC and dA with equal frequency calculate information content during DNA replication in the given sequence. "
     As an example I choose ATCGGCT and changed it to 10% deamination of dG.
PROPOSED SOLUTION:
For sequence ATCGGCT,
I am only consider the initial strand bases A,T,C are 2 bits a base, given by I=-1/ln(2)ln(n_before/n_after) ,where n_before = 1, and n_after = 4
In the case of mutated G (Gm) ,
I say, I = -1/ln(2)ln(1/3)= 1.58 bits , n_after=3 since A,C are equivalent to Gm
Perfect copy would give us 7 bases x 2 bits each = 14 bits content of strand.
Since there are 2 G's, with 10% change of mutating --> 0.02 of G in strand will mutate.
Thus I content during replication,
    Information content I(ideal) - I(inc. mutation) = 14-0.03 = 13.97 bits during time of replication

Sounds like a homework question. Have you already tried to solve this yourself? If so then it would help if you show what you have tried and why you think it is incorrect (or correct).

"the mutation rate of G's is 10 %" what does this phrase mean? For example, are you saying that for every cell division a G residue has a 1/10 chance of mutating (and that the other bases have a 0/10 chance of mutating?)? In this model, what base does a G mutate into? One of the other 3 bases, randomly? "The most common mutation product binds with C and A" this phrase does not have a clear sense to me. Since there are only 3 choices, G could mutate into A or C or T, but none of those will bind with C and A with equal frequency, do you see what I mean?

Since DNA is double-stranded, if the sense strand is 5'-ATCGGCT-3' then the antisense strand (or reverse complement) will be 5'-AGCCGAT-3', so there are two G's on the top strand and two more G's on the bottom strand, did you take that into account?

This sounds like computing science/statistics rather than biology. Where does this mathematical formula you quote for information content come from? I've never heard of it and I can't see how it relates to anything 'real' in  genetic information.

I think I have a solution..
I am only considering 1 strand based on original problem wording, however mdperry I did consider the second strand. I am glad you also brought that up.
David the formulas come largely from (https://schneider.ncifcrf.gov/paper/ri/latex/ )
So my soluion

Thanks @Valentin-Angelo Uzunov. More mathematics than computer science even. I'll pass on this one.

So I think you have answered the question yourself. While I am no expert, I think Schneider presents the most thoughtful, and clearest descriptions and explanations in his many publications on this subject. I also appreciate your clarification of the question, and now understand the answers to the points I raised. 14 bits for a 7-mer sounds correct to me.  I don't really understand what a student is supposed to learn from doing this exercise, with the mutations etc. but I suspect you have the answer they are looking for.

I guess we will find out.
Actual sequence was AGCCGATTTGGGAAAAATCG, = 40bits without. 2bit / base.
When 20% mutation of G is taken into account.
If 20% of G will be mutated, then that = 1.2 bses ~ 1 based in the sequence will be likely mutated during replication
The information content of a mutated G = 1.58 bits. thus, deltaI for that bit is 2 - 1.58 = 0.42 bit lost from mutation
Thus information content is 40 - 0.42 = 39.6 bits during replication.
That is my final answer.


text:
Potential homogeneity across cell membrane
During respiration, individual bacteria (and mitocondria)  produce a relatively large potential difference (∼100 mV) between the inside and outside, using energy to pump $H^+$ out of the cell to the liquid environment (a proton motive force is created). Together with proton pumps, or sources, also sinks of protons are present, channels which reuse the voltage difference for other goals.
Imagine a cell like a bag, with only very few and sparse sources and sinks of protons. At the limit, take only 1 source and 1 sink, diametrically opposed, which continuously work. Is it reasonable to assume that the voltage difference created is homogeneous in space (it has same value everywhere along the surface)? How would this depend on the size of the cell?
My guess is that the homogeneity of the voltage should depend on the speed of diffusion of protons in water, which I imagine is extremely fast (but how fast?). So all variations around the mean value would be washed out on very short time scales (shorter than the shortest times of μs−ms
which are biologically relevant). But I may miss something. Any insight will be appreciated.

what is the question exactly?

The main question is Is it reasonable to assume that the voltage difference created is homogeneous in space (it has same value everywhere along the surface)?

it depends on the process you are looking for http://www.ncbi.nlm.nih.gov/pubmed/20566861 for example. Look for images in bacteria using voltage-sensitive dyes/proteins. Problem to do it is resolution


text:
Preferred criteria for new bee colony location
As a human I want a house with a roof, indoor plumbing, bug free, and make my wife happy.  I don't want to drive too far to work, and it has to be well-suited for offspring.
What are the criteria that define a "good spot" for a new location for honey bees.  I'm sure it involves water, shade, access to nectar, and defensibility, but I don't know any of the details.
Has anyone ever made measures of this? Beekeepers? Apiologists?  What are the things bees think are important, and what values of those do they think are "best"?

According to Thomas Seeley, in his book, Honeybee Democracy, he gives the following as important criteria for honeybees when selecting a nest site when a bee colony moves to swarm:

Larger volume (the minimum nesting capacity was found to be around 14 liters with more preference to nests with a capacity of approximately 30 to less than 100 liters)
Relatively small entrance (10 to 30 centimeters squared)
Nest with the entrance located near the floor of a tree cavity
Direction of the nest entrance (south facing for thermoregulation during the winter)
Nest height (preference given to higher nests for colony defense)
Remnants of previous honeycombs (saves work and energy in building the nest structure)

Interestingly enough, bees did not necessarily display a preference for the shape of the entrance, the shape of the nest, the draftiness or dryness of the nest cavity (they are able to plug and waterproof nests).
Flower/nectar/food availability is not necessarily a direct factor as this changes quite frequently throughout the seasons and honeybees are not able to leave their honey stores (which are necessary to sustain the colony throughout the winter) or take them with them every time the colony has trouble finding food. Honeybees have a complex and efficient system for optimized location and sharing of food sources, therefore distance is not as large a factor.

I assume you're talking about keeping honeybees apis mellifera , not other species.
Beekeepers often move there hives around to follow nectar availability, so I assume nectar availabilty is considered the most important factor.
In my country the first to flower is willow salix. After that they move to cherry&plum tree plantations and after that to appel&pear.


text:
Can the restless leg syndrome may have been caused due to natural selection?
Disclaimer: I don't know how much restless the leg has to be, in order to be considered a syndrome.
RLS runs not only in my family but also several people in the locality. My hypothesis is that RLS is a genetic/epigenetic adaptation to prevent mosquitoes or other insects from sucking blood. I, indeed, live in a malaria zone. I don't know enough biology to device a scientific experiment to prove my hypothesis.
Is there any scientific research done in this field? Someone who is well versed in this field should try it.


text:
Are there viruses that show definite enzymatic activity?
Perhaps due to outer coat protein individually or collectively.

Yes even the smallest viruses have enzymes. like reverse transcriptase/integrase in retroviruses. Your question is unclear.

I think he's talking about the intact virus particle. I suspect the answer is no, as the initial aim of the virus particle on infection is to get into the cell, and until it does that substrates will be thin on the ground. But Nature's always full of weird oddities, so who knows?

@David Influenza virus, for example, has neuraminidase on its coat.

@WYSWYG Not even weird. I'd forgotten that the virus particle needs to get out of the cell as well as get in (which I gather is the function of neuramidase).

@WYSIWYG I add a chemical with virus particles, without the help of cellular machinery will the virus be able to transform the chemical? Are there such virus? That was the question. You have answered affirmative with an example. Thanks. Is this common?

@AhmedAbdullah You should edit your question to add all relevant details. From the question it is not clear what you mean to ask. If you clarify the question then it can be reopened.

As some of the comments mention, this question could use some clarification.
First, assuming you're asking in general about enzymatic activity in viruses:
A few classes of "non-autonomous" viruses (particularly endogenous retrotransposons) don't encode any enzymatic functions and sometimes don't even encode their own structural proteins - they rely on the structural proteins and/or enzymatic functions of the "autonomous" viruses.
With the exception of those non-autonomous viruses, all retroviruses encode the reverse transcriptase and integrase functions, while many non-retroviruses (those which don't have a step in their lifecycle where they convert RNA into DNA) also have RNA-dependent RNA polymerase activities.
Now, assuming you meant to limit your question to the viral coat (AKA capsid) proteins of an intact virus-like particle (VLP):
Most do not have any "enzymatic" activity per se - they do not catalyze the formation or breakage of any covalent bonds. However, many viral coat proteins have membrane associated domains which undergo conformational changes essential for uncoating and trafficking of the virus across the membrane:
Gao, D., Lin, X., Zhang, Z., Li, W., Men, D., Zhang, X., & Cui, Z. (2016). Original Article: Intracellular cargo delivery by virus capsid protein-based vehicles: From nano to micro. Nanomedicine: Nanotechnology, Biology, And Medicine, 12365-376. doi:10.1016/j.nano.2015.10.023
This membrane translocating (aka cell penetrating) activity sometimes does depend on the "collective" action of oligomeric complexes of capsid proteins, but it is not an enzymatic activity.
However, the parvoviruses do encode a phospholipase enzymatic activity in their coat proteins which serves to disrupt cellular membranes and allow viral entry:
Kobiler, O., Drayman, N., Butin-Israeli, V., & Oppenheim, A. (n.d). Virus strategies for passing the nuclear envelope barrier. Nucleus-Austin, 3(6), 526-539.
I don't know of any other classes of coat proteins with bona fide enzymatic activity, but I wouldn't be surprised if some exist, and I've only touched on a few of the multitude of enzymatic activities exhibited by other viral components.

There are other examples of enzymatic activity in the capsid such as the neuraminidase of influenza virus.


text:
Can I figure out the identity of my grandparent from this information?
I know all my family up to my grandparents, with the exception of the grandfather on my mother's side. At the time my mother was conceived, my grandmother was having an affair so no one in my family knows for sure who the grandfather was.
In high school we learnt that blue eyes are a recessive trait and brown eyes are a dominant trait, as such I should be able to figure out who my grandfather is, but I only studied up to that level and I want to check with someone more knowledgeable than myself if it is correct.
So here's my reasoning:
I have blue eyes, meaning I have two blue eyed genes and got one from my father and one from my mother.
My mother has brown eyes, meaning that she has one brown eyed gene and one blue eyed gene to pass it on to me.
My grandmother has blue eyes, so she passed one on to my mother.
One of my potential grandfathers had blue eyes, so if it had been him my mother would have received two blue eyes genes and have blue eyes. But she has brown eyes so it must be the other potential grandfather (who's eyes I don't know the colour of).
Can someone tell me if this is correct, and if not, why not?

All of your grandparents could have been brown eyed. Your having blue eyes only requires that one grandparent on the maternal and one on the paternal side were carriers. Note though that eye colour is not as simple as dominant and recessive.

Related: Is it possible for a brown eyed parent to have blue eyed child?

You are trying to work out who your mother's father was. You know that your mother's mother had blue eyes, but your mother had brown eyes. You also have blue eyes. You make an assumption that eye colour is a Mendelian trait, with a dominant brown allele (A) and recessive blue allele (a) such that AA and Aa are brown-eyed, while aa gives blue eyes.
To have blue eyes you must have gotten an a from each parent, so your mother (who is brown-eyed) must have been Aa. You know that her mother was aa, because she had blue eyes. Your mother must have inherited her A from her father, therefore, your mother's father had brown eyes.
Can this information identify your grandfather? Maybe, depending on the list of candidates (e.g. you have two men and you know that one of them is the grandfather, and one has blue eyes, the other has brown eyes). However, it's based on an assumption that eye colour is a Mendelian trait, with a dominant brown-eye allele and recessive blue-eye allele, and that a mutation has not occurred which gave your mother brown eyes. That assumption is flawed, eye colour is not Mendelian (it's polygenic), and you cannot rule out mutation in eye colour genes. That said, you are more likely to resemble the people you are more closely related to, so resemblance in eye colour could offer some clues (as would other easily visible characteristics like skin type, hair colour, hair type, facial features, height, physique). In short, you cannot identify your biological grandfather by eye colour, but it may give some slight indication.
See also:

Blog post on eye colour genetics (with referenced papers here and here)

One of my potential grandfathers had blue eyes, so if it had been him my mother would have received two blue eyes genes and have blue eyes.

No, this does not necessarily follow, because eye color genetics are more complicated than just one dominant-recessive gene. See, for example this article from a someone at  Stanford University on How Blue Eyed Parents Can Have Brown Eyed Children. It isn't common, but apparently it does happen.
Solving your inheritance just based on eye color with 100 percent certainty is not possible.

On a high-school level you are right. Still, the answer to your question is no.
As you may have already noticed, nothing in reality is as simple as schools tell us. Eye colour is generally determined by one gene, but there are other genes which can modify the effect. Think about this question: if there were just two alleles, blue and brown, where would green-eyed and grey-eyed people come from?
If you want to investigate your who is your biologic father, you can ask them both to take a genetic test. If they decline or cannot comply, try comparing many traits, not just one. Ask for photographs of you mother and both possible fathers when they were your age and make a list. What is everybody's hair colour? What is their height? What is the shape of their faces? the proportions of bodies? the skin colour? shape of mouth, nose, eyes? Do you know everybody's blood type? Maybe you just look a lot like one of the men, then you can assume he's your father. Maybe you look a lot like your mother and there are only subtle differences which point to one of the men? Remember that this comparing does not give you certainty, only clues.


text:
Does size matter?
As I compare the morphologic differences between mouse models and the human disease for which they are analogous, I have become interested in what difference interspecies size has on molecular function.  For example, the mouse colon has a diameter of 1 mm, the human 75mm it seems to me there should be many genetic/transcription differences between species just as a pup-tent (analogous to a mouse) requires a much different support structure than a 10 story building (analogous to a human) yet I find little about this in the literature, can someone help or show me where this has been addressed?  Thanks!

It would be useful if the title question was more revealing of what is actually being asked

The renowned biologist JBS Haldane was concerned with the problem of size and wrote about it in his essay of "On being the right size". Two situations he discusses may be of interest.
The first is that large animals are not just scaled-up versions of smaller ones. He calculates the weight-bearing ability of bones to show that the increase in cross-section of bone in a scaled-up person could not accommodate the increase in "weight per square inch". The conclusion here, I think, is that a different type of structure is required to deal with the weight of a larger animal. In the sort of molecular genetic terms that did not then exist, one would need a different program of transcription.
A second situation relates to the size of eyes and the size and number of rods and cones they contain. Here he argues that there is little intrinsic difference between the cells that make up the eyes of mice and men (this is 1926), despite the difference in number (and hence eye size). In this case the gene transcription would be expected to be similar.
He also talks about the modification of lungs and gut to provide a required increase in surface area in larger animals. This would seem similar to the case you raise. Is this more of the same or a fundamental difference? I leave it to you to decide.
The original essay is out of copyright and can be found on the web. However you might also be interested in a printed collection that includes other of Haldane’s essays as well.

@MattDMo Point taken. I've rewritten my answer entirely.

looks good! Could you include a link to the online version of the essay as well?

@MattDMo I've done that now.


text:
Embryo development terms
I'm trying to couple the following terms:
cytoplasmic determinants, induction, positional information, hox genes, pattern information, morphogenisis, determination and differentiation.
I hope someone can explain me the connection between these terms,
thankyou,

When in doubt go back to definitions I say (as I am now).
cytoplasmic determinants: regulatory molecules located in specific distributions around egg cytoplasm
Induction: process by which the presence of one tissue influences the development of others
positional information, signals cells about its relative position to other cells.
hox genes
Differentiation: the process of a cell becoming a specialized type of cell through regulated gene expression
Determination: process by which portions of the genome are selected for expression in different embryonic cells
Pattern formation (aka morphogenesis) → events that determine the spatial organization of an embryo
Hox genes establish anterior posterior axis and regulate gene expression.
I would change,
cytoplasmic determinants → differentiation via determination → pattern formation (rather than information)
morphogen lead to pattern information (since these are the signals)
hox genes → morphogens → pattern information → pattern formation


text:
What are the secondary structure requirements for cell-penetrating peptides AKA protein transduction domains
Cell penetrating peptides.
Cell penetrating peptides (CPPs) are a class of short amino acid sequences which are sufficient for crossing cell membranes and delivering themselves along with any attached cargo into the cytoplasm of cells. They were branded CPPs recently, while the term "protein transduction domain" (PTD) was used in the early days of their study, when the necessary sequences were being isolated from native proteins with cell-penetrating activity (notably, HIV-1 Tat).
Most of the scientific literature I have found on CPPs focuses on their potential relevance for targeted drug delivery, and mostly discusses the delivery of proteins and nanoparticles via fusion of CPPs to the N-terminus of the target protein. The only Stack Exchange question & answer on CPPs also points to a discussion of N-terminal fusion of CPPs to a cargo peptide. However, research on cell penetrating peptides has come a long way since the 2005 article referenced in that post.
The 2012 Milletti review highlights that there has been a dramatic increase in the number of different classes of cell penetrating peptides, including hydrophobic CPPs, primary amphipathic CPPs, alpha-helical amphipathic CPPs, beta sheet amphipathic CPPs, and proline-rich CPPs, among others. And that is just between 2005 and 2012! The Milletti 2012 article also covers some CPPs isolated from other viruses.
I have not been able to find a review of similar detail written since, although I'm sure much progress has been made in the field.
Although it is not my main question, I would appreciate any citations for more recent reviews which go into detail on the molecular mechanism of cell penetration for one or more classes of CPPs - especially a review of the function of PTDs in their native proteins.
I have only begun to research CPPs and PTDs in their native proteins and in the drug-delivery setting because it became apparent that a protein I am studying for an undergraduate thesis may have an internal PTD which is essential for its function. I am no expert on the topic and I would appreciate information on CPPs/PTDs including further synonyms for CPPs/PTDs to aid in my literature search - especially synonyms specific to native proteins with CPP-like functions.
What are the secondary structure requirements for cell-penetrating peptides?
My question is whether the previously described positively charged CPPs and/or the new classes of CPPs described in Milletti 2012 are only functional as N-terminal fusions, or whether they typically function efficiently when they are incorporated within an internal loop (in terms of primary sequence, but still exposed to the solvent). The 2005 article cited in the previous Stack Exchange question on this topic stated that the CPP derived from HIV-1 Tat is based on residues 47-57, which are internal residues of the 86 amino acid protein - a protein which has cell-penetrating activity in its native role in HIV-1 infection.
Therefore, my question is not whether or not this ever occurs - it clearly does - but to what extent do CPPs isolated from internal sequences of native proteins have CPP-like functions in their native proteins?
The system I am studying for my thesis is a virus, so any information specifically on CPPs and PTDs function in the native proteins of viruses would be particularly useful.

References
Jones, S. W., Christison, R., Bundell, K., Voyce, C. J., Brockbank, S. M. V., Newham, P., & Lindsay, M. A. (2005). Characterisation of cell-penetrating peptide-mediated peptide delivery. British Journal of Pharmacology, 145(8), 1093–1102. http://doi.org/10.1038/sj.bjp.0706279
Milletti, F. (2012). Review: Cell-penetrating peptides: classes, origin, and current landscape. Drug Discovery Today, 17850-860. doi:10.1016/j.drudis.2012.03.002
Vivès, E., Brodin, P., & Lebleu, B. (1997). A truncated HIV-1 Tat protein basic domain rapidly translocates through the plasma membrane and accumulates in the cell nucleus. The Journal Of Biological Chemistry, 272(25), 16010-16017.
If anyone interested in answering this question is not an expert, the best resource I can currently provide for a list of CPPs derived from natural proteins (besides the Milletti 2012 article above) is:
Hallbrink, M., Kilk, K., Elmquist, A., Lundberg, P., Lindgren, M., Jiang, Y., & ... Langel, U. (n.d). Prediction of cell-penetrating peptides. International Journal Of Peptide Research And Therapeutics, 11(4), 249-259.

I will be continuing to research this topic for my thesis, so if you're interested in answering this question but require more information, feel free to comment asking for specific information that would help.
Thank you!

This is a very interesting and thorough question. Although I don't have an immediate answer I'd be interested to know more about CCPs. I'd like to know more about cargo and membrane insertion. Please feel free to respond in the biosphere (and ping me using @James) since comments are not really intended for extended discussion. (Also, I've made some stylistic edits to your question, feel free to roll back!)

@Demosthenes' pars triangularis Are you still in the field of CPPs research?


text:
How the genome assembly be done after k-mer counting?
As far I know, before assembly of a genome, all k-mers from read should be counted.

But after that, how the genome assembly be done?
Is there any other thing needed along with k-mer counts?
How the standard value of k is determined for a particular genome assembly? or is it fixed for all kind of assembly?

I just want to know the basic concept that how this actually been done. Explanation with flow char or algorithm is much more appreciated.
I went through some similar question, but those did not help me too much.

There are multiple ways of doing genome assembly.
The term you are probably looking for is "De Bruijn-Graph based assembly". Using this you can find a lot more different explanations of how it is done.
Another frequently used method is "Overlap Layout Consensus assembly", which in fact is not based on k-mer counting.


text:
Why is chlorophyll green? Isn't there a more energetically favorable color?
Chlorophyll being green means it absorbs light in the red and blue area of the spectrum. Isn't this the high and low energy light? Wouldn't plants get more energy if they absorbed light in the green area of the spectrum instead of the red one?

The reason that chlorophyll is green is because it absorbs other colors of light such as red and blue, so in a way the green light is reflected out since the pigment does not absorb it.
Because life might have been purple:

It is possible that the very first life form to process light may have been purple colored. This would mean it was reflecting red and blue light and absorbing green. In such a scenario this thing if it was the first to produce energy from light would have out competed against everything else. It would have had a population explosion and possibly covered much of the Earth or at least the oceans. Haloarchaea are an example of a simple life form that uses Retinal and Bacteriorhodopsin to produce energy though far less efficiently than photosynthesis. Had this been developed prior to photosynthesis it may have let it spread very far even though it is a less efficient energy production method. A 2% efficiency increase in a market no one has yet tapped is still a huge advantage.
In this scenario because the first thing to use light was using green light it left a niche for another form of life to exploit. That niche would have been absorbtion of the Red and Blue spectrums. Which is the same area plants absorb today. They got so good at their niche that they eventually were able to generate much more energy than the first life form did and eventually out competed for the sun. This niche has worked so well that they never developed a full system for the other spectrums.

Because you could say that good enough is good enough:

The sun puts out a lot of energy. It is possible that there was no need to try and capture all of the spectrum or that it was actually not beneficial to do so. Often too much sun is more an issue than too little. Too much sun and heat can dry out the plant. It is possible that to gain the benefits of photosynthesis there needed to be a reduction in some energy to balance it out. Much like a black car on a hot summer day a black plant might absorb all of the spectrums but also get far too hot. Blue plus red may just be the sweet spot.

However, about your question about colour:

Wouldn't plants get more energy if they absorbed light in the green area of the spectrum instead of the red one?

Plants would probably get more energy if their leaves were black.
Sources:

https://www.quora.com/Why-did-chlorophyl-evolve-to-be-green-as-opposed-to-black-which-would-absorb-more-energy
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691134/
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2807594/

That first sentence basically says, "chlorophyll is green because it isn't some other color."

@amarillo feel free to edit my answer.

Absorbing higher energy may also lead to harmful photoproducts.

"Because you could say that good enough is good enough" -- this is perhaps the most important point.  If there was a massive benefit to doing so, plants would likely have evolved to capture the green spectrum as well.  But doing so would probably not help -- a lack of sufficient CO2 to use all the captured energy would almost certainly be the result.

@Yoda Plants already absorb blue, which is more energetic than green.


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Red transcriptional reporter in Psudomonas putida
I need to build a transcriptional reporter in P. putida with high excitation wavelength,in order to decrease phototoxicity (I have been using mNeonGreen until now,  and I would like to try something red).
My colleagues reported to me that previous tries with mCherry and mKate2 failed because:

mCherry seems to have a very long maturation time, not suitable for
my experiments
mKate2 did not show any expression at all

Does anybody have experience with transcriptional reporters in P. putida?
Any ideas? (DsRed? re-try with mKate?)
I am measuring the expression of a PsrI (sigma factor for siderophore production) regulated gene.

What about RFP (red homologue to GFP)?


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Under what circumstances does Batesian mimicry evolve?
Batesian mimicry is a form of biological resemblance in which a noxious, or dangerous, organism (the model), equipped with a warning system such as conspicuous colouration, is mimicked by a harmless organism (the mimic). An example would be unrelated species such as Myrmarachne plataleoides, the spider, and the weaver ant Oecophylla smaragdina.
Given that evolution is a random process that doesn't have any pre-defined targets the probability of such convergence in evolutionary history should be nearly zero. My argument is that the search space for a 'nearly optimal' Batesian mimic would be too large and hence any search algorithm would be unable to avoid the curse of dimensionality. Even the sampler, which would
need to sample from a wide variety of valid phenotypes in the parameter space would run into serious problems.
The problem of the curse of dimensionality for optimal sampling can be intuitively explained in the following way:

Let's say you have a straight line 100 yards long and you dropped a penny somewhere on it. It wouldn't be too hard to find. You walk along the line and it takes two minutes.
Now let's say you have a square 100 yards on each side and you dropped a penny somewhere on it. It would be pretty hard, like searching across two football fields stuck together. It could take days.
Now a cube 100 yards across. That's like searching a 30-story building the size of a football stadium.
The difficulty of searching through the space gets a lot harder as you have more dimensions.

Here are additional points to clarify what I mean:
My question is whether the Batesian mimic would need to initially be quite similar in morphology to the different species that it's converging to in morphology. In mathematical terms, if the parameter space for the visible morphological features is $(x_1,x_2,...,x_n) \in \mathbb{R}^n$ then convergence is probable if and only if the initial condition lies in a small enough neighborhood of the solution $(q_1,...,q_n)$.
One of the features of the fitness function is that I think there should be exponential payoffs in terms of reproductive success near the solution $\vec{q}$. Further, I think there are probably other very important environmental factors that might lead to such convergence. An arboreal jumping spider of similar size that shares the same environment as leaf-cutter ants is a good example. They would already have similar color among other features in order to blend in the same environment.

Well it is not too hard for it to evolve, because it has evolved, many times. What is your question? See my answer here regarding (what some people suggest are implausible) rates of evolution and adaptation. http://biology.stackexchange.com/questions/45005/approaches-towards-a-theory-of-innovation-in-evolution?lq=1

One of the (several) problems with your conclusion is that you assume the initial adaption needs to be "nearly optimal" to start with.  Assume instead that looking 1% more like a coral snake provides a harmless species with a 1% improvement in reproduction. Modeling that leads to efficient mimicry within a relatively short number of generations.

There are no question mark in your question :) It is a sign that the question is probably unclear.

@iayork What do you mean by 1% more? Let's just look at a silly example. Let's suppose you're just comparing two 3 dimensional shapes. How does a square become 1% more like a sphere?

@rg255 My question is whether the Batesian mimic would need to already be quite similar in morphology to the different species that it's converging to in terms of morphology to start with. In mathematical terms, if the parameter space for the visible morphological features is $(x_1,x_2,...,x_n)$ and we assume that each of these variables are differential functions of a parameter $t \in [0,1]$ then convergence is probable if and only if the initial condition lies in a small enough neighborhood of the solution $(q_1,...,q_n)$.

@rg255 This can probably be modeled as a monte carlo simulation once we have defined a suitable fitness function. One of the features of the fitness function is that I think there should be exponential payoffs in terms of reproductive success near the solution $\vec{q}$. Further, I think there are probably other very important environmental factors that might lead to such convergence. An arboreal jumping spider of similar size that shares the same environment as leaf-cutter ants is a good example.

@Aidan Rocke How does a cube become 1% more like a sphere? It rounds off the corners a little bit, obviously.   How is this a difficult concept? The same applies with mimicry.  The whole point about evolution is that tiny advantages, compounded, become large advantages.

@iayork Your argument is actually false. Show me the computation that determines that a cube is '1%' more spherical when its corners are rounded. Now, in general how are you supposed to do such a calculation of 'percentage similarity' assuming that some of the variables are independent from each other and some are strongly correlated.

@iayork There are many ways for a cube to become more 'spherical' but the computation would involve some distance measure not a percentage. If you're serious about saying anything correct about shape similarity measures you might like to google that first. But, I must say that this question is much more complicated than that. If you can't do a good job analyzing such a problem then I wouldn't join this discussion.

You're an engineer, aren't you.  Engineers, dentists, and physicists are notorious for (1) not understanding evolution, and (2) being too arrogant to try to learn about it.  As a result, they make incredible fools of themselves bloviating about things they don't understand.

@iayork it might be best to step away from the comments here, I don't think the mods will appreciate the way the thread is going.

@AidanRocke it's rarely good to try reducing evolution to computation, it's far more complex. I think the (very appropriate) point iayork is trying to make is that the mimic species doesn't evolve by jumping from a state of dissimilarity to perfect mimicry, but gradually becomes a better mimic - in other words, it will slowly evolve to look more and more similar to the species it mimics.

@rg255 I actually understand that point. But, my question is whether there must be special restrictions on the initial conditions in order to guarantee that such convergence is possible. There might be an advantage for a baboon to look like a lion for example as it wouldn't be bothered as much by hyenas and leopards but the cost makes such an evolutionary trajectory improbable. In some sense the morphological parameters of the mimic must initially be within a neighborhood of the morphological parameters of the target animal.

Then essentially your question is why doesn't mimicry always evolve - for example, why don't baboons evolve to look like lions? In such a case you are right, they look really different so it's hard (but not impossible) for evolution to produce that mimicry... see here: http://biology.stackexchange.com/questions/35532/why-do-some-bad-traits-evolve-and-good-ones-dont/35658#35658 and here: http://biology.stackexchange.com/questions/7932/why-are-there-no-wheeled-animals

@rg255 That's a related question. My question is under what circumstances does mimicry evolve. And can these conditions be made precise to a certain degree? Answering why mimicry doesn't always evolve is easier than explaining under what circumstances it might evolve.

Well the only requisite would be the presence of heritable genetic variance affecting phenotype, such that the two species could carry genes which have similar phenotypic results. Selection is not even a requisite, but it does help a lot; really good mimicry is less likely to evolve purely by random processes of evolution (e.g. drift). Even with selection favouring mimicry we cannot say that mimicry will evolve.

Mimicry and camouflage is an extremely efficient defense. If an insect gains a color fleck that makes it 1 percent less likely to be eaten, that color fleck will grow, diverge and change over generations.

While the attempt to consider this in a mathematical framework perhaps isn't so useful, it seems that the biological essence of your question is along the lines of:

Does a Batesian mimic initially need to be initially quite similar in morphology to the different species which it evolves to mimic?

The answer is no, morphology does not need to be similar, but it does help make mimicry likely. The only requisite to evolution is the presence of heritable genetic information with the potential for change, and this prerequisite is the same for any trait. Selection is not a prerequisite but mimicry is more likely to evolve by adaptive evolution than random evolution. Given that phenotype is often strongly affected by the DNA and that DNA has a potential to mutate, then any distance in phenotypic space can be covered so long as sufficient mutations occur. Sufficient mutations are more likely to occur when
a) the distance in phenotypic space between the two initial species is small (the ancestral form of the mimic species is similar to the species it will mimic)
b) a large amount of time is allowed to elapse (more mutations can occur)
The first of these is simply stating that there are fewer (or less extreme) mutations required to get the species to be perfect mimics. The latter simply states that time allows for a greater number of mutations to occurs, making it more likely that large phenotypic spaces can be bridged.
Consequently, allowing identical time, mutation rates, mutation effect sizes, and selection coefficients, two species that initially look similar are more likely to evolve mimicry than two species that initially look very different, because fewer steps need to be taken for convergence of phenotypes.
This is the same for any trait. One could ask can humans evolve to be ten feet tall, the answer is yes, as long as the genetic variance arises. One could ask can humans evolve to be 20 feet tall, and again the answer is yes. However, the latter is less likely because it requires a greater movement in phenotypic space. More time also makes both results more likely.

This answer seems reasonable. but, would you mind expanding on point a)? I mean can we quantify how small this distance must be in order for evolution of Batesian mimicry to be probable within a few generations?

It would involve too many assumptions that would be violated in nature, there's a major problem with trying to reduce some evolutionary problems to equations - nature is just too complex

I can take a look at point a tomorrow - it's explained a little in the last paragraph when comparing 10 and 20 feet tall people (as a very simple univariate example) - but if you want me to expand further then remind me tomorrow (bedtime here!) @AidanRocke


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Which strand of a gene specifies a protein?
A gene is a segment of DNA (I hope double stranded) and each strand when transcribed form a mRNA and after being translated a protein. As from each gene there are two proteins that are being formed. Now how do these two proteins determine the expression of the gene?
I may be wrong. Please explain if so.

Usually (I don't know about any counter examples), only one of the DNA strands encodes a mRNA.

@Maljam What happens to the other strand ? Why is it not transcribed? How does a cell know which strand to transcribe and which strand not ?

Genes have promoters and enhancers upstream of the start site, all on the same strand. It is not unusual to have two (sometimes completely different) genes overlapping in a certain segment of DNA.

All enzymes related to DNA require a 3'-> 5' strand as they can synthesize product only in 5'-> 3' direction. Same happens with RNA polymerase too. It synthesizes mRNA in 5'-> 3' direction and thus requires only 3'-> 5' strand of DNA.

If a piece of DNA were to be transcribed on both strands, at the same time, the transcription complexes would collide and inhibit each other, like steric hindrance.
If you could overcome this interference and synthesize primary transcripts from both strands, it follows that the two RNAs would hybridize to each other and form complementary RNA-RNA hybrids.  These dsRNAs are very poor substrates for translation by the ribosomes. This was the initial mechanism proposed for anti-sense RNA to down regulate gene expression.
In many, if not most, EUKARYOTIC cells, a dsRNA will trigger the siRNA/shRNA/miRNA response mediated by Dicer et al. leading to degradation of both RNA strands.
So in virtually all instances, only one strand will be transcribed, and encode a mRNA with a significant ORF.

But this only applies to eukaryotes. Prokaryotes do have overlapping ORFs and don't have the dicer system.

Normally only one strand of DNA is transcribed. This is possible because for the RNA polymerase to bind and start transcribing the DNA into mRNA (or pre-mRNA) a special sequences on the DNA called a promoter is needed. Promoters will normally only be positioned to allow transcription in one direction, i.e. of one DNA strand.
Bacteria and their viruses sometimes have slightly overlapping genes so that, depending on their direction, the end of one mRNA may be from the same stretch of DNA as the start of another. This may not matter if one or both is not translated in this region.
There are even some cases where the end of one protein is from the same stretch of DNA as the start of another, but the amino acid sequences are different because they come from opposite strands. In such cases one assumes that the sequence of the protein is unimportant in that particular region. One does generally find most variation in the N- and C-terminal regions of homologous proteins in different species.


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Why haven't prey evolved the ability to always outrun their predators?
I can understand why some prey can't outrun a recently evolved species. However, since cheetahs have existed for so long, why haven't its prey evolved to always outrun it, driving cheetahs to extinction. Is it because the cheetah population size is so much smaller than the population size of most of its prey species that its prey species are under very weak natural selection to outrun cheetahs? Is it that those that can run faster have more other biological costly traits?

what will stop predators to evolve to always catch their prey?

There are limits to how fast a given animal can go.  Prey also tend not to run in straight lines so there are many ways to improve via evolution.... there are no supersonic animals for instance!

For further reading check out the Red Queen Hypothesis

An alternative (facetious) question: "Why haven't they evolved wings to just fly away?" I've marked this question as a duplicate of "If a trait would be advantageous to an organism then why hasn't it evolved yet?"

What prevents predator overpopulation? explains the dynamic between preys and predators in absence of evolution. That may interest you.

Just remember, not all prey are at their peak physical fitness all the time. Just because a cheetah caught one one doesn't mean it could have caught any. In other words, perhaps all prey actually can out run a cheetah, but not when they: are sick, pregnant, juvenile, in the middle of taking a dump, half asleep, critically dehydrated, in unfamiliar territory etc... What I'm getting at is that your assumption that "caught and eaten" = "can't out run a cheetah" is not necessarily accurate

The same way, if prey "evolved" to always outrun their predators... the predators would simply start attacking their young, who can't outrun them yet. Which actually happens all the time, so prey animals "learned" to protect their young (e.g. herding). Running faster doesn't help you protect your children - and prey animals who run away while letting their children get eaten don't pass their traits on future generations.

They don't have to outrun their predators, they just have to outrun their friends!

@James Before I read your comment I was going to reply with "Of course they've evolved, we have birds don't we?", in jest of course :)

If prey were never caught by their predators then they would not have predators. The question is essentially meaningless if taken literally (e.g. "always").

predators cull the week from the herd, allowing the strong increased access to food and mates. while unfortunate for the eaten animal, it is beneficial to the long term success of the species. and that is all your genes care about.

I have decided not to vote to close: much of the material is covered in the duplicate but this question also relies heavily on co-evolutionary arms races which is not covered in the other question.

"Evolution is a journey, not a destination."  In other words, they're working on it; give them time.  (Meanwhile, they're hoping cheetah's don't evolve jetpacks.  Although I'm not, because cheetahs with jetpacks are cool.)

can't believe this question got 6 answers. People need hobbies

@aaaaaa Or some predators chasing them away from their computers.

The main thing to get is that there is no end game for evolution. (and that its not a competition) Its an ongoing process of species adapting to changing circumstances.

Maybe the preadator prey system is an evolutionary stable strategy. There's a biological cost for the prey running away faster because doing so burns more energy and it's not definite that it will get eaten if it doesn't. If the preadator population size is larger, the prey evolve to run away faster because they need less risk of being eaten on each chase in order to survive and reproduce and that reduces the preadator population size.

I think this might actually be an unsolved problem. None of the answers fully explain why they don't always outrun their predators. Ell's answer doesn't explain why the cheetah and gazelle system appears to be stable without gazelles evolving to be even faster at running away. Surely some people are so smart that they could actually figure out the answer to this question.

There are (at least) three important factors to consider here; evolution under selection requires genetic variation upon which to act, selection can act on covarying traits causing trade-offs, and adaptation also occurs in the predator. A lot of this is covered elsewhere on this site (including the effects of the other mechanisms of evolution), but little specific reference is made to predator-prey co-evolution.
Adaptation and genetic variance
One of the mechanisms of evolution is selection, and adaptation occurs when species evolve as a response to selection. For a response to selection to occur there must be genetic variation within the trait, such that the genes an individual carries affect the individuals fitness. For example, there may some genes which give the carrier better muscle structure for fast running, and this increases survival which, in turn, increases reproductive output. The importance of genetic variation is often overlooked, but is highlighted by the breeders equation. Genetic variance can arise by novel mutations, or can exist as standing genetic variance.
Selection on covarying traits
Selection is seldom, if ever, a univariate process. That means fitness is not determined by a single characteristic, so fitness in a prey species may be determined by the speed at which it can run, but also its metabolic rate, stamina, ability to acquire nutrients, the way it provisions nutrients for growth and repair etc.. Genetic covariance between traits (induced by linkage or pleiotropy) can impact the response to selection, because any selection acting on a covarying trait can cause affect the adaptation occurring in the focal trait (strengthening, weakening, neutralising, or even reversing the direction of response). Therefore, if running speed covaries with other traits it may be difficult for selection to increase running speed. Think about athletes, I doubt Usain Bolt could run 10,000 metres as fast as Mo Farah and vice versa, because there is a trade-off between speed and stamina.
Adaptation in other species
If selection did cause speed to increase in the prey species then that would strengthen selection for increased speed in the predator. This is called an evolutionary arms race, where the adaptive the evolution of two species interacts causing adaptation and counter-adaptation. For example, genes which allow faster running might spread through a population of gazelles (prey) because carriers are more likely to outrun the lion (or the other gazelles), but this will increase selection on lions (predator) to increase speed (or adopt other strategies) which will spread genes to make the lions faster (use other strategies); the result being adaptation and counter-adaptation between the gazelle and lion populations.

There is a little series here about Butch Brodie and his studies of coevolutionary arms races between garter snakes and toxic newts. It would be good to read on the Red Queen Hypothesis, which describes how species, under interaction with other species, must continue to evolve just to prevent extinction. Also worth noting that prey species often have more than one predator species (and predator species often have more than one prey); interaction and coevolutionary networks are complex. What may be adaptive in some interactions may also be maladaptive for other interactions (see specialist and generalist, and selection on covarying traits).

Good answer, but for readability I would restructure it and put the arms race/RQH parts at the top, since those issues are most targetted to this particular question. Genetic variation and covariation/trade offs are always an issue in evolution, but more general than the coevolution between predators and prey.

Maybe it would. I put it this way around to introduce the concept of adaptation as a response to selection first before talking about how subsequent adaptation can affect selection in other species. I also put the comment at the start regarding predator-prey co-evolution to highlight it's importance from the outset.

Assuming the animal books I read as a child didn’t lie to me, the peregrine falcon and pigeon might be a rather insightful example of an arms race, since (the book asserted) the two birds’ body shapes are similar because the shape is well-adapted to high speed, and the peregrine falcon is so fast because of its constant need to maintain a speed advantage over pigeons. (That factoid really captured my interest and has stuck with me, so here I am rather confident that if incorrect, it is the book’s fault and not my memory’s. :P)

When looking at what's evolutionarily favorable, you need to keep in mind that predator-prey relationships are rarely a simple binary.  For example, evolving speed to out-sprint the lion won't help if you're being chased by a human who will keep pursuing until you drop from exhaustion.

The snake / newt arms race was the first thing I thought of when I read the question.

I don't understand why it seems like the cheetah and gazelle system is stable and gazelles aren't evolving to run away even faster. Do you know a more detailed answer of the different reasons a prey species gets eaten by predators as often as it does? If so, can you edit your answer to explain it?

There are two reasons for this: evolutionary trade-offs and coevolution (the "Red Queen hypothesis", as mentioned in the comment above by Luigi).
Evolutionary trade-off describes situations where one trait cannot increase without a decrease in one or more others. Some hypothetical examples:

longer legs may help run faster, but past a certain point, it will increase the risk of injury, decreasing survival;
lower body weight may increase top speed, but past a certain point, it will decrease starvation tolerance;
more muscle may help acceleration but will increase energy requirements.

All changes have costs and benefits. In situations where the outcome of an event is simply "success/failure", there is therefore an evolutionary incentive to evolve to be just good enough. Once you are good enough getting better only increases the cost (I am oversimplifying this a bit).
Change in an extrinsic driver will change the balance of cost and benefit, shifting evolutionary pressure. For example, when predators are absent (island populations) birds sometimes become flightless, because one benefit of flight (escape from predators) no longer applies.
The interesting bit happens when the "extrinsic driver" is another living thing that is also capable of evolving. In this case you suddenly get an evolutionary arms race where each side is constantly subject to a selective pressure to be slightly better than the other, which is a moving target. You therefore get an arms race situation (or the extinction of one or the other side). The Red Queen hypothesis is named after a quote by the Red Queen in "Alice through the looking glass" (Carroll, 1871):

Now, here, you see, it takes all the running you can do, to keep in
  the same place.

Using the example of a lion and a gazelle: lions run fast enough to catch and eat the slowest gazelles. The remaining gazelles are on average faster, for whatever reason(s). Some of those reasons will be heritable and the next generation of gazelles will be faster. The slowest lions will starve, and some of the reasons for the remaining lions being faster will be heritable so the next generation will be a bit faster, and then you're back where you started. Rinse and repeat.
Predation obviously operates on a much faster timescale than selection, so this doesn't always occur (putting a fox in a chicken coop won't evolve fast chickens).
Coevolutionary "arms races" can be seen in predator-prey interactions, mimicry and much more (including for example the evolution of sex, but that's off-topic for this answer).

I would use the leopard as an example which actually is fully in this arms race.

To what extend would e.g. a 5% increase in the speed of all the gazelles in an area affect predation?  I would think that in many cases, the primary limiting factor on the speed of animals caught by lions is the speed of the slowest prey animal.  Once the lion has caught the slowest animal, the remaining animals will be safe from that lion for awhile.  Unless a species gets fast enough to outrun some other prey species, it's unlikely to get fast enough for all its members to outrun predators.

@supercat:  the old joke, I don't need to outrun the bear, I just need to outrun you.

Predators always have to be much better hunters than the prey - they must eat every few days after all. But they can only get so good.
Predator/prey population balance will tend to look like a competition where if the predators are too efficient they will kill off the prey.  If that happens they start to starve to death.
If the prey outrun the predators (or at least escape all the time) then the predators will starve to death.  Then they breed until there are so many that they eat all the grass/vegetation and then they die off.
While both of these have certainly happened in natural history what is more stable for predators and prey to evolve in competition with each other such that their populations look like a stable equilibrium. If not, one of the would just disappear.  Then later via migration another animal would come in to replace them.

The first paragraph sounds a little wrong and seems to contradict the so called "life-dinner principle".