User talk:Opabinia regalis/Archive 8
This is an archive of past discussions about User:Opabinia regalis. Do not edit the contents of this page. If you wish to start a new discussion or revive an old one, please do so on the current talk page. |
Archive 5 | Archive 6 | Archive 7 | Archive 8 | Archive 9 | Archive 10 | → | Archive 15 |
And now, for Fvasconcellos' traditional nonsectarian holiday greeting!
A user has somehow reverted your edit on Netzarim and Netzarim (disambiguation). Could you revert back to yours. Thanks. --Shuki (talk) 00:33, 8 February 2009 (UTC)
Help your fellow scientists?
Hi, Tim Vickers and I and a few others have been invited to give workshops that may turn dozens of research life scientists into actively contributing Wikipedians. I've been impressed by your Featured Articles for the MCB WikiProject, and I would be grateful if you could help us. Would you be willing to answer a few questions of these nascent editors by private e-mail? I realize that you're de facto retired from Wikipedia, but I don't think it will take much of your time and any help would be at your leisure (i.e., flexible schedule). If you would like to help us, please e-mail me for details. Thanks! Proteins (talk) 23:20, 27 June 2009 (UTC)
Thanks for the peer review. Many good points that will help improve the article. Much appreciated. --Scott Free (talk) 23:00, 13 July 2009 (UTC)
I have nominated Sequence alignment for a featured article review here. Please join the discussion on whether this article meets featured article criteria. Articles are typically reviewed for two weeks. If substantial concerns are not addressed during the review period, the article will be moved to the Featured Article Removal Candidates list for a further period, where editors may declare "Keep" or "Remove" the article's featured status. The instructions for the review process are here. —Mattisse (Talk) 01:01, 2 August 2009 (UTC)
Hi!
I just ran across a peer review you did and I rushed over here. Every once in a while I check your user talk, but it is always so quiet. I hope you are going to edit less "sporadically" now! :) Awadewit (talk) 14:40, 2 August 2009 (UTC)
- Heh, and here I was thinking 'sporadically' would be an upgrade! :) Good to hear from you again though. I've started to get more involved in other 'open science' type efforts, so it seems logical to pick up wiki editing again... or it would, if only I had a few more hours in the day! Opabinia regalis (talk) 20:20, 2 August 2009 (UTC)
Coalesence theory
This is going to sort of be out of the blue, this formula does not seem to be correct. Here is an example of the output
- N=10
- t = 1 to 20
- p(1) = 0.047561471
- ....
- p(21) = 0.017496887
Above is an approximation of what the curve should look like. I am not sure but I think the it should be 1/t since the lambda is based on rate which is 1/t. I didn't change the formula, just wanted to know why it is not working.PB666 yap 04:51, 27 August 2009 (UTC)
- You happen to have caught me at a good time! Hmm, couple of issues here.
- 1) There is a typo in the formula; should be because we're doing the calculation for generation t.
- 2) This is a bad approximation for such small values of t and N as in your calculations.Opabinia regalis (talk
- 3) The equation has the form , where the expectation value is beta ( = 1/lambda = 2N). I don't quite understand your graph - probability of fixation isn't the same as probability of coalescence. Opabinia regalis (talk) 05:29, 27 August 2009 (UTC)
- Agreed but the 2N is frequently quoted as the time in generations to the MRCA. I know what the problem is I just dont know how it can be solved. The problem is that the exponential distribution assumes that any individual in a population can produce population size in one generation, which may be true if the population size is small or partuition rates are high. So for example in the graph above there are limits on progeny, producing a single female is 0.5 and two female 0.25. I have done this also were I have extended the distribution outward to as many as 6 female offspring in a balanced distribution, the results are similar to the above. Because there is a finite limit on progeny production (I think the record is 35 females in a population of 6 billion trials) one can create a poisson distribution to estimated the probability of X number of females. Therefore a given trial p(1)~ 0.5, p(2), . . . . p(35) = 0.000000000001 p(50) = 0. IOW for a population of 50 females it is impossible that all females will coalesce to one female in the next generation. For a population of 2500 females it is impossible for that the population coalesce to one female in 2 generations, however with the above formula the highest probability is in the first generation, ergo the formula contradicts observation. I suppose if we had Speckled Trout in a Bay, and a single trout could produce 1 million eggs, and there are less than a 1/2 million female trout in the bay then it is possible. I have tested this with Monte Carlo analysis several years ago (right after Vigilante published) and did a reanalysis after doing some modeling against some stone age life expectancies. The demonstrated that some females needed to produce more than 6 offspring for the population to remain stable in size. The graph above is close even if we extend progeny outward and if one consider 100s of generations the median of the cummulative distribution is at ~2.6N. I can show you a paper where these curves are used. I want to recapitulate the curves for an image, but I can't seem to find the formula (that way I am not WP:COPYVIO). I would hate to have to run a Monte Carlo analysis for 11,000 individuals and 5 million years (heh-heh).PB666 yap 16:16, 27 August 2009 (UTC)
- This coalescence distribution is asking the question how long before any two random individuals will have the same parent, OK so but for a gene quasi-fixed in the extant population we are asking the question how far back to we have to go such that all extant members share an ancestor, and that is the first ancestor all share together. So that traveling down the tree there is the probability that two individuals are related in the next generation by several probabilities 1, the female had 2 female offspring (lets just say p(0)=0.25, p(1)=0.5), p(2)=0.25 therefore 1/2 of the individuals in the population can be paired to a common ancestor in the previous generation and half cannot, the process continues backwards until we reach the TgMRCA. If we make the assumption that by chance all of individuals have a valid sibling of the same sex in all generations of the lineage then minimum coalescent time is log2N in generations. The probability of fixation in T generations is p(2)^(Sumi=0 to T-1 2i) where
N is a value of 2,4,8,16,...... I think you can see what I am getting at.PB666 yap 16:25, 27 August 2009 (UTC)
I found the formula, its in Wakely [1]:
where
This is from Tavare (1984) and BTW if you know what it means or how to convert it to microsoft excel equation it would be greatly appreciated :^) (I think I can figure it out, I'll put that little metal hat on my head and bzzzzz).PB666 yap 21:38, 27 August 2009 (UTC)
- Don't use the above formula, they have substitute N, population size with n, number of alleles, they have substituted T with t which is the number of branch times. I have tried to applied both versions of the formula and the answer was always 0.PB666 yap 16:47, 29 August 2009 (UTC)
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And now, for FV's traditional last-minute nonsectarian holiday greeting!
Happy New Year!
The article Geoffrey Chang has been proposed for deletion because of the following concern:
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GA reassessment of Multiple sequence alignment
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Proteasomes are very large protein complexes inside all eukaryotes and archaea, as well as in some bacteria. In eukaryotes, they are located in the nucleus and the cytoplasm. The main function of the proteasome is to degrade unneeded or damaged proteins by proteolysis, a chemical reaction that breaks peptide bonds. Enzymes that carry out such reactions are called proteases. Proteasomes are part of a major mechanism by which cells regulate the concentration of particular proteins and degrade misfolded proteins. Proteins are tagged for degradation with a considerably small protein called ubiquitin. The tagging reaction is catalyzed by enzymes called ubiquitin ligases. Once a protein is tagged with a single ubiquitin molecule, this is a signal to other ligases to attach additional ubiquitin molecules. The result is a polyubiquitin chain that is bound by the proteasome, allowing it to degrade the tagged protein. The proteasomal degradation pathway is essential for many cellular processes, including the cell cycle, the regulation of gene expression, and responses to oxidative stress. The importance of proteolytic degradation inside cells and the role of ubiquitin in proteolytic pathways was acknowledged in the award of the 2004 Nobel Prize in Chemistry to Aaron Ciechanover, Avram Hershko and Irwin Rose. (more...)
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RNA interference (RNAi) is a system within living cells that takes part in controlling which genes are active and how active they are. Two types of small RNA molecules – microRNA (miRNA) and small interfering RNA (siRNA) – are central to RNA interference. RNAs are the direct products of genes, and these small RNAs can bind to other specific RNAs (mRNA) and either increase or decrease their activity, for example by preventing a messenger RNA from producing a protein. RNA interference has an important role in defending cells against parasitic genes – viruses and transposons as well as gene expression in general. The RNAi pathway is found in many eukaryotes and is initiated by the enzyme Dicer (pictured), which cleaves long double-stranded RNA (dsRNA) molecules into short fragments of ~20 nucleotides that are called siRNAs. Each siRNA is unwound into two single-stranded (ss) ssRNAs, namely the passenger strand and the guide strand. The passenger strand is degraded, and the guide strand is incorporated into the RNA-induced silencing complex (RISC). The selective and robust effect of RNAi on gene expression makes it a valuable research tool, both in cell culture and in living organisms because synthetic dsRNA introduced into cells can induce suppression of specific genes of interest. (more...)
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