I guess that as a CAFA organizer, I should really contribute to the second page. And I will. But I really don’t mind if someone else jump-starts it.

http://en.wikipedia.org/wiki/Protein_function_prediction

http://en.wikipedia.org/wiki/Critical_Assessment_of_Function_Annotation

1. Men don’t tell the truth about their penis. No kidding? But this is somewhat more serious. It has been accepted for some time that male circumcision dramatically reduces the rate of HIV infection. But recently, some reports have shown that high rates of infection prevail among circumcised men as well. But since circumcision is usually self-reported, could there be a problem there? This study shows that in a cross-sectional (sorry…) study among recruits to the Lesotho Defense Force, 50% of the men that reported they were circumcised were, in fact, partially (27%) or completely (23%) not circumcised. The researchers conclude that biases in the self-reporting of male circumcision may lead to erroneous reports that show high HIV infection rates among circumcised men.

Concluding quote:

…until further research can document improved methods for obtaining accurate self-reported MC [male circumcision I.F.] data, all assessments of MC and HIV prevalence, as well as projections for VMMC [voluntary male medical circumcision I.F.] interventions, should be informed by physical-exam-based data [as opposed toself reporting, I.F.].

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0027561

Can sharing data help prevent errors and fraud?

From the abstract:

Background: The widespread reluctance to share published research data is often hypothesized to be due to the authors’ fear that reanalysis may expose errors in their work or may produce conclusions that contradict their own. However, these hypotheses have not previously been studied systematically

So Jelte Wicherts and his colleagues from the University of Amsterdam wanted to see whether sharing data was related to the number of statistical analysis errors in a paper. So, to phrase this as a null and alternative hypothesis:

H0:There is no difference in the number of statistical errors in those papers where the authors are willing to share data, and those where the authors are unwilling to do so.

H1: (one sided): the number of weaker evidence and statistical errors in papers where the authors are unwilling to share data is larger than those in which the authors are willing to share data.

Wicherts and colleagues contacted authors of 141 papers published in five journals of the American Psychological Association, requesting their data. Trouble is, they could not get enough authors to share data to make their own study significant: in a previous study, some 73% of the authors contacted were unwilling to share data. Wow.

However, authors publishing in two of these journals, Journal of Personality and Social Psychology (JPSP) and Journal of Experimental Psychology: Learning, Memory, and Cognition (JEP:LMC), were somewhat more forthcoming.  Wicherts and colleagues therefore limited their analysis to a subset of 49 papers published in those journals. (Note that sometimes lack of data sharing is due to legitimate considerations, such as being part of an ongoing study, or third-party proprietary rights. However, those were not considerations in 49 papers analyzed here.)

Wicherts  then checked for specific types of statistical errors in these papers, and compared the number of errors in papers from authors willing to share data to those who did not. Here are some of the findings:

Distribution of the number of errors in the reporting of p-values for 28 papers from which the data were not shared (left column) and 21 from which the data were shared (right column) for all misreporting errors (upper row), larger misreporting errors at the 2nd decimal (middle row), and misreporting errors that concerned statistical significance (p<.05; bottom row). doi:10.1371/journal.pone.0026828.g001

Pretty clear picture: those papers where the authors authors were willing to share data were less prone to statistical errors.

Concluding quote:

In this sample of psychology papers, the authors’ reluctance to share data was associated with more errors in reporting of statistical results and with relatively weaker evidence (against the null hypothesis). The documented errors are arguably the tip of the iceberg of potential errors and biases in statistical analyses and the reporting of statistical results. It is rather disconcerting that roughly 50% of published papers in psychology contain reporting errors [33] and that the unwillingness to share data was most pronounced when the errors concerned statistical significance.

Although note that Wicherts is very careful about drawing conclusions:

Although our results are consistent with the notion that the reluctance to share data is generated by the author’s fear that reanalysis will expose errors and lead to opposing views on the results, our results are correlational in nature and so they are open to alternative interpretations. Although the two groups of papers are similar in terms of research fields and designs, it is possible that they differ in other regards. Notably, statistically rigorous researchers may archive their data better and may be more attentive towards statistical power than less statistically rigorous researchers. If so, more statistically rigorous researchers will more promptly share their data, conduct more powerful tests, and so report lower p-values. However, a check of the cell sizes in both categories of papers (see Text S2) did not suggest that statistical power was systematically higher in studies from which data were shared.

In fact, Wicherts also wrote a piece in Nature where he argued that sharing data can help avoid fraud, such as in the recent infamous case of Diederik Stapel, a highly regarded psychologist at Tilburg University in the Netherlands.

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0026828

3. Toilet paper. A study of surfaces of public restrooms has shown that they are covered with bacteria, mainly the kind that is known to live on and in humans. So now we have a somewhat broader view of the species living in restrooms, including the uncultured ones.

Two interesting quotes from the paper:

Although many of the source-tracking results evident from the restroom surfaces sampled here are somewhat obvious, this may not always be the case in other environments or locations.

Not sure about this bit: if the sources here are obvious, then is this paper a proof-of concept?

Also:

Unfortunately, previous studies have documented that college students (who are likely the most frequent users of the studied restrooms) are not always the most diligent of hand-washers.

No shit! (Pun intended).

Concluding quote:

Although the methods used here did not provide the degree of phylogenetic resolution to directly identify likely pathogens, the prevalence of gut and skin-associated bacteria throughout the restrooms we surveyed is concerning since enteropathogens or pathogens commonly found on skin (e.g. Staphylococcus aureus) could readily be transmitted between individuals by the touching of restroom surfaces.

Translation:

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0028132

Thomas, A., Tran, B., Cranston, M., Brown, M., Kumar, R., & Tlelai, M. (2011). Voluntary Medical Male Circumcision: A Cross-Sectional Study Comparing Circumcision Self-Report and Physical Examination Findings in Lesotho PLoS ONE, 6 (11) DOI: 10.1371/journal.pone.0027561

Wicherts, J., Bakker, M., & Molenaar, D. (2011). Willingness to Share Research Data Is Related to the Strength of the Evidence and the Quality of Reporting of Statistical Results PLoS ONE, 6 (11) DOI: 10.1371/journal.pone.0026828

Flores, G., Bates, S., Knights, D., Lauber, C., Stombaugh, J., Knight, R., & Fierer, N. (2011). Microbial Biogeography of Public Restroom Surfaces PLoS ONE, 6 (11) DOI: 10.1371/journal.pone.0028132

from Bio import SeqIO
from itertools import izip_longest
# Loop over pairs of reads
readiter = SeqIO.parse(open(inpath), "fastq")
for rec1, rec2 in izip_longest(readiter, readiter):
    print rec1.id  # do something with rec1
    print rec2.id  # do something with rec2
    .
    .

izip_longest is fed the same iterator, readiter, twice. However, readiter.next(), which advances the iterator, is called on the first argument and then on the second argument. Since next() is being called on the same iterator, successive records are yielded.

By “merged file” I mean a fastq file where the mate-pairs are one after the other, as in:

@HWUSI-EAS687_112864999:8:1:1980:1055#CGAGAA/1
GTTTGTTTTAATTTCAGTGATTCATCAATTTTAAAAAAAGATGAGAATAATAACTATTATAAAAAGATAAATAAATGTGAAATTTATATTTCAAATTCAA
+
@:DGBGDDD@GGGDGDGDDGD@GGGGE@GGG?EBGGGADDDDGEG4?3BA*::7:GEGGGG>EDDDDAG@G><ADDGBGGGGEGGGGDGGGFEGGGEFDE
@HWUSI-EAS687_112864999:8:1:1980:1055#CGAGAA/2
AATGAATTGAATAAATATAAGAAGGATGATTAATAATAATTCTTGAATTTGAAATATAAATTTCACATTTATTTATCTTTTTATAATAGTTATTATTCTC
+
D?DB:@8EBDB>GG:=<DED79>>A8CEC8DGDGG8CEC<BGGG+BAAEA@D<2D71;:8AG<ABBEEEEBEDC?C>AACDDDCD>AD<@EFFDDDECBB
@HWUSI-EAS687_112864999:8:1:2274:1058#CGAGAA/1
CCTCAGTTAGCTTCTATTGGTATTAACATGGGTGAATTTACTAAACAATTTAATGACCAAACTAAAGATAAAAATGGTGAAGTTATACCTTGTATAATTA
+
GFGGGHHGHHHHHHGHHHHHGHHHHHHHFBGDBGEHHHHFHHEHHHHDFHCGFFFHHHHHHHGHHGGEBHEEFFCEE@E>A>>8A@EBE@BBB>BGEEDB
@HWUSI-EAS687_112864999:8:1:2274:1058#CGAGAA/2
AACTGGAGTTGTTTTAATTTCAAAAGTAAAAGATTTATCTTTAAATGCTGTAATTATACAAGGTATAACTTCACCATTTTTATCTTTAGTTTGGTCATTA
+
IIIIIIIIIIGIIIDHHIIIIDIHD8CGGGGDADEIIIIIIIHIIGBGD>DGDGGDGIGIIIIBGDG@GFHIIII<C<CCGHHHIHIBGDEEB3BEDEE@

The solution is derived from this Stackoverflow entry.

Of course, if the mate-pair files are not merged then you can use this script to merge them. Also illustrates using iterators from two different files in one for loop:

#!/usr/bin/env python
from Bio import SeqIO
import itertools
import sys
import os
def merge_fastq(fastq_path1, fastq_path2, outpath):
    outfile = open(outpath,"w")
    fastq_iter1 = SeqIO.parse(open(fastq_path1),"fastq")
    fastq_iter2 = SeqIO.parse(open(fastq_path2),"fastq")
    for rec1, rec2 in itertools.izip(fastq_iter1, fastq_iter2):
        SeqIO.write([rec1,rec2], outfile, "fastq")
    outfile.close()

if __name__ == '__main__':
    outpath = "%s.merged.fastq" % os.path.splitext(sys.argv[1])[0]
    merge_fastq(sys.argv[1],sys.argv[2],outpath)

The Friedberg Lab is recruiting graduate students, for both Master’s and Ph.D.

WE ARE:  A dynamic young lab  interested in gene, gene cluster and genome evolution, understanding microbial communities and microbe-host interactions by metagenomic analyses, developing algorithms for understanding gene cluster evolution, and prediction of protein function from protein sequence and structure.

YOU ARE: an independent, hard-working problem-solving, energetic and motivated scientist-to-be. You have graduated or are about to graduate in computer science and/or biology or related fields. The Friedberg Lab is a “dry” lab, so some programming skills are required (Python preferred).

Existing and planned projects include:

1. Computational protein function prediction and assessment of function prediction algorithms. The Friedberg Lab is among the leaders of the Critical Assessment of Function Annotations (CAFA), an international effort of dozens of research groups to asess and improve function prediction algorithms. We are looking for students that are excited about prediction of protein function from sequence and structure. Also, how well can we assess how well our algorithms are doing? The next CAFA meeting will take place in Berlin, July 2013 and the Friedberg Lab will play a central role in  answering these questions.

2. Metagenomics:  we are studying the interaction between the microbiome and the host using metagenomic and metatranscriptomic data. In collaboration We are looking at how the human microbiome affects gene expression in the host. Together with Robb Chapkin’s lab at Texas A&M we are analyzing microbial genomes and their effect on transcription in the human gut. We are also developing algorithms for context-based function prediction in metagenomic data. Simply put: how well can we prediction the function of a gene from its neighbors? Since many of the genes in metagenomic data have no known homologs, we are developing creative ways to computationally discover their function.

3. Microbial Evolution: we are researching the evolution of Mycoplasma, a bacteria genus which serves us as model clade for understanding genome evolution. Mycoplasma have the smallest genomes of any organism, and being parasitic evolve quickly. Together with the Balish Lab we expect to sequence several new species and strains in the next year, and we are developing computational methods and a central community database  for analyzing the Mycoplasma tree of life. Besides the biological aspect, this project is also a great opportunity to get into web programming, database design, and learn how top design and code community-based scientific software. 

4. Biopython: Biopython is a set of freely available tools for biological computation written in Python by an international team of developers. It is a distributed collaborative effort to develop Python libraries and applications which address the needs of current and future work in bioinformatics. If you would like to become a Biopython developer, part of an international community of open-source scientific software developers, the Friedberg Lab is the place for you. This option is especially attractive for Master’s students seeking to enter bioinformatics in Industry.

5. Insert your brilliant idea here! I love new projects!

The lab is equipped with its own 10-node cluster computer, several workstations, and has access to Miami University’s Supercomputing Center, and the Ohio Supercomputer Center at Ohio State University.  Students have an excellent research environment, and many opportunities to collaborate with labs on and off campus.

Students can apply to the Friedberg Lab via the following graduate programs at Miami University:

1. Microbiology (Master’s and PhD).

2. Cell, Molecular and Strcutural Biology (PhD only).

3. Computer Science (Master’s only).

You are welcome and encouraged  to inquire further. I love talking with prospective students. If you would like to set up a phone/Skype chat please send your CV to:

friedberg.lab.jobs ‘at gmail ‘dot’ com

Looking forward to hearing from you.

Iddo Friedberg, PhD

Assistant Professor, Microbiology and Computer Science (affiliate)

Miami University

Oxford, OH, USA

Recently MIRA seemed to have developed a stochastic bug, one of those which are a serious headache to track down. Bastein called upon the MIRA community to help him. A couple of weeks ago, the “bug” was resolved to everyone relief. It was not a bug at all, but … well, I’ll let you read Bastien’s letter. Probably th funniest and geekiest error report I have seen since, well, ever. Reproduced here from the mira_talk email list with Bastien’s permission. WARNING: fairly geeky and fairly long. Not for everyone. But if you, like me, enjoy a good story travails of extreme bug hunting, I guarantee you will not be disappointed. (Because we have all been there, although personally I don’t recall encountering a problem that frustrating). Teaser: it was not a bug.

Dear all,

]]> http://bytesizebio.net/index.php/2011/09/02/5389/feed/ 0 http://bytesizebio.net/index.php/2011/08/31/postdoc-positions-available-at-rutgers-university/ http://bytesizebio.net/index.php/2011/08/31/postdoc-positions-available-at-rutgers-university/#comments Wed, 31 Aug 2011 15:01:14 +0000 Iddo http://bytesizebio.net/?p=5369 Postdoctoral Research Scientist

Rutgers University

Joint Appointment: Institute of Marine and Coastal Sciences, BioMaPS and
Dept. of Biochemistry and Microbiology

Two 2-3 year Postdoctoral Research Scientist positions are available.
We are looking for young scholars with experience in the areas of
computational biology. In the scope of this project, we will uncover how
the metal-containing enzymes responsible for the critical electron
transfer reactions that turn basic elements such as H, O, C, S, and N
into biologically active molecules have evolved. The position will
involve developing new sequence and/or structure based bioinformatic
approaches to (1) mine available databases for proteins responsible for
bio-catalyzed electron transfer reactions, (2) establish evolutionary
relationships between extracted sequences and structures and (3)
generate hypotheses for how the electron transfer circuitry arose and
now functions. Candidates should have a PhD in Computational Biology or
Bioinformatics. Candidates with degrees in related fields (e.g. biology,
computer science) and possessing the necessary skill-sets are welcome to
apply. We strongly encourage applications from recent PhD graduates.
Strong programming skills (at least one of: Perl, Python, or Java) are
essential for these positions, as well as, some familiarity with the
major bioinformatics tools and databases. Experience in machine
learning algorithms is desired, but not required. Candidates should be
fluent in spoken and written English and should be able to communicate
ideas and results to colleagues from all the diversity of life sciences.
The ability to integrate into a team is as essential as that to complete
a project without constant supervision.

Interested persons should e-mail a cover letter and C.V. to:

Dr. Yana Bromberg,
Dept. of Biochemistry and Microbiology,
Rutgers University
e-mail: yanab ‘at’ rci ‘dot’ rutgers ‘dot’ edu

Sometimes, gene duplication occurs within a species: part of the chromosome may be duplicated, causing one, a few, or many genes to have more copies of themselves within the species. The descendants of the duplicates and the original are homologous are they are descended from a common ancestor. This type of homology is called paralogy: a homology due to a duplication event (para == in parallel).

In another case, the genes can be homologous due to speciation: a new species (A1) diverges from the original (A0), carrying highly similar genetic loads. The gene for, say, brown eyes in A1 and the gene for brown eyes in A0 are also homologous: derived from the gene of hemoglobin in A0. This time, the homology is called orthology: it is not due to in-species duplication, but due to speciation itself (ortho == exact).  The definitions of orthologs and paralogs were given by Walter Fitch in a seminal paper published in 1970.

One of the first protein structures to be solved was that of hemoglobin, the oxygen carrying protein complex in our blood. Scientists noticed that hemoglobin in jawed mammals has three different protein chains: alpha, beta and gamma. Their amino acid sequences were very similar, suggesting that the genes encoding for hemoglobin are highly similar, suggesting homology. Since all jawed mammals have hemoglobin, and they all had alpha, beta and gamma chains, the conclusion was that the duplication of the original genes happened in the common ancestor of  jawed mammals, before they split up into different species. Hence, the alpha, beta and gamma chains in hemoglobin are paralogous: homologous due to duplication preceding speciation. However, gamma-hemoglobin was shown to have a different function than beta or alpha (more on that in a bit).  The conclusion from this observation was the Ortholog Conjecture and it can be stated as follows: paralogs (reminder: homologs due to duplication) diverge in function more than orthologs (homologs due to speciation). A model was proposed for this observation: when genes duplicate within a species’ genome, there is less selective pressure on one copy to perform the same function. Thus, it can accumulate mutations and eventually adopt a different function. The ortholog conjecture states that paralogs mostly differ in function, whereas orthologs mostly do not. The ortholog conjecture is a very powerful statement because, if we have two proteins known to be orthologs, we can infer that they have the same function, whereas paralogs may not (if they had enough time to diverge). The ortholog conjecture is therefore a fundamental tenet in molecular phylogenetics, and is also a tool used to predict the function of proteins. If two homologous proteins are found out to be orthologs, then it is assumed they have the same (or highly similar) functionality.

A crack in the ortholog conjecture was formed in study published late 2009 in a paper published by Romain A. Studer and Marc Robinson-Rechavi. I blogged then about their study:

Romain A. Studer and Marc Robinson-Rechavi challenge common wisdom by publishing a study that says: “it ain’t necessarily so”. They look at three alternative models of molecular function evolution: (i) subfunctionalization after duplication; (ii) neofunctionalization after duplication; and (iii) the ‘alternative model’ of equal change after duplication or speciation. Subfunctionalization holds that after duplication, each of the two copies of the gene performs only a subset of the functions of the ancestral single copy. Neofunctionalization holds that one of the two genes possesses a new, selectively beneficial function that was absent in the population before the duplication. The ‘alternative model’ states that the gain of new function is not preferential to paralogs and that orthologs may gain new functions at the same rate that paralogs do.

Studer and Robinson-Rechavi claim that few studies have been made to study the scope of any of these proposed models. They then lay out study designs for doing so, challenging other evolutionary biologists (and themselves?) to conduct these studies and examine whether the common wisdom that orthologs maintain function while paralogs gain function. What I like about this paper is that it not only makes a strong case for challenging conventional wisdom, it also lays out a series of possible routes of study to be taken up by others.

Now two studies have widened this crack to a rather large crevasse. The first is a study by scientists in Indiana University. In a way, this new publication is a response to Studer & Robinson-Rechavi’s call to arms on points (i) and (ii). The IU scientists (the Radivojac lab and the Hahn lab at the School of Informatics at Indiana University, Bloomington, IN) examined hundreds of pairs of orthologous and paralogous genes from the mouse and human genomes. They then examined whether paralogs had a higher functional similarity, or rather orthologs.  What they found certainly defied the ortholog conjecture:

The relationship between functional similarity and sequence identity for human-mouse orthologs (red) and all paralogs (blue). (A) Biological pathway (B) molecular function. From PLoS Comput Biol 7(6): e1002073 under CC licence.

But before we explain the results, a word about function. The function of a protein has several aspects which are context-dependent; two important ones are the molecular function of the protein, and the biological process in which it participates. For example, the molecular function of all hemoglobins  is noted as  oxygen binding and oxygen transport. However, they are different in the processes, or pathways, in which they participate: gamma-hemoglobin participates in the transport of oxygen in the fetus. The complex which contains gamma-hemoglobin has a higher affinity to oxygen, and thus able to extract oxygen in the placenta from the maternal oxygenated hemoglobin and transport it to the fetus.

Now we can explain the figure above. Graph (A) above shows the functional similarity for the biological pathway aspect and how it is affected by the sequence identities of the hundreds of orthologs (red) and paralogs (blue) examined between human and mouse. Graph (B) shows the functional similarity of the molecular function aspect.

The X-axis is the sequence identity percentage between any pair of sequences: the higher the percent identity, the less divergent are the sequences, the more inclined we should be to think that the pair of proteins performs the same function since they diverged less. The Y-axis shows the fraction of functional similarity. Looking at graph (B) above, we see that paralogs which are 100% identical, have (almost always) the same function . But sequences of orthlogous proteins between human and mouse have only about 65% functional similarity, on average. What does that mean? In the database they looked at, each gene has a set of words associated with it, describing what it does. The IU scientists found that only about 65% of the keywords in orthologous sequence pairs overlapped, on average. Whereas for paralogs 100% overlapped. And those are for sequences which are identical! This means that even if we find identical protein sequences in human and in mouse, it does not mean that they have the same molecular function. On the other hand, paralogs, will generally have more similar functions. So the ortholog conjecture has been stood on its head here: paralogs are the ones that would generally have the same function, whereas orthologs diverge more in function. This holds true for up to about 50% sequence identity, when the picture seems to reverse itself. Graph (A) depicts the differences in the biological pathway aspect. Here, the differences are even more striking. The paralogs which are 90-100% identical between human and mouse participate in almost exactly the same pathways in both organisms. But orthologous proteins which are 90-100% identical the functional similarity is much lower:  only about 65%.

So what does this all mean?

First, it means that, at least between human and mouse, paralogs are better predictors of function than orthologs. And why would that be? To answer this question, let’s look closer at the graphs above. Note that while for paralogs the functional similarity decreases rapidly with sequence similarity, for orthologs the functional similarity remains roughly the same no matter how similar or different the orthologs are to each other, and even when they are 100% identical their functions vary to some extent! The reason: the experimental study of function in two human and in mouse  takes place in different contexts. The species-specific context is what causes the differences in annotation, and in the overall function. Also, all the orthologs in the study are of the same age, dating back to the human-mouse lineage split 75 million years ago. The paralogs predate that split, and may be of different ages: the split may predate the human / mouse split by 10 million years, 100 million years, or 1 billion years. Thus orthologs, regardless of their actual sequence similarity, have the same age, and paralogs do not. But why should proteins of the same age share the same level of (not so high) functional similarity? The authors of the study reply:

While there is no direct role for “time” in evolution that is not tied to mutation, we suggest that what time represents here is the evolution of the cellular context: the sum of the evolutionary changes over all of the directly and indirectly interacting molecules. If this context evolves at a steady rate (i.e. the average amount of functional change among all of the interacting molecules remains relatively constant), then protein function will appear to evolve at a steady rate, a rate largely disconnected from the level of an individual protein’s sequence divergence. — PLoS Comput Biol, Vol. 7, No. 6.

The strongest evidence they find for this hypothesis, is that even proteins with 100% are annotated differently. To wit:

For example, Liao and Zhang [50] found that >20% of genes that are essential for viability in humans are not essential in mouse. It is unlikely that changes to the proteins themselves have made them essential or not, but rather that their context in cellular and organismal networks has evolved. –ibid.

The proteins may not have changed substantially, but their environment changed, giving them a different role. Think about changing jobs after moving to a new place where there is no employer providing your exact old job you were used to. You may have been an embedded systems programmer, but now you are a website programmer. So context goes a long way to explain changes in ortholog function.

Interestingly, about a month after the IU paper was published, another paper from the Robinson-Rechavi lab was published, which also talks about homologs between human and mouse. In this study Gharib and Robinson-Rechavi reviewed previous literature listing several types of functional divergence of orthologs between human and mouse. They had some additional findings. For example, about 11% of the orthologous genes were alternatively spliced, meaning that the end products, proteins, were different between human and mouse.  They also listed specific phenotypic effects: genes which are linked to diseases in humans, but mutations in their mouse orthologs have no effects on mice. They cite studies that found that over 20% of genes which are essential in human are non-essential in mice (an essential gene is just that: if the organism does not have it, or it is mutated, the effects are fatal, and the organism does not develop past very early stages).  Their literature review concluded that 10-20% of ortholog pairs between human and mouse cannot be used for functional transfer. The IU study implies a higher percentage. Both studies conclude that a common practice in molecular evolution studies, the use of orthologs to infer function, should be seriously looked at.

(Full disclosure: Dr. Radivojac & I are collaborators, although our collaboration is unrelated to this study).

Nehrt, N., Clark, W., Radivojac, P., & Hahn, M. (2011). Testing the Ortholog Conjecture with Comparative Functional Genomic Data from Mammals PLoS Computational Biology, 7 (6) DOI: 10.1371/journal.pcbi.1002073

Gharib, W., & Robinson-Rechavi, M. (2011). When orthologs diverge between human and mouse Briefings in Bioinformatics DOI: 10.1093/bib/bbr031

Fitch, W. (1970). Distinguishing Homologous from Analogous Proteins Systematic Zoology, 19 (2) DOI: 10.2307/2412448

#!/usr/bin/env python
from Bio import SeqIO
import itertools
import sys
import os
# Copyright(C) 2011 Iddo Friedberg
# Released under Biopython license. http://www.biopython.org/DIST/LICENSE
# Do not remove this comment
def merge_fastq(fastq_path1, fastq_path2, outpath):
    outfile = open(outpath,"w")
    fastq_iter1 = SeqIO.parse(open(fastq_path1),"fastq")
    fastq_iter2 = SeqIO.parse(open(fastq_path2),"fastq")
    for rec1, rec2 in itertools.izip(fastq_iter1, fastq_iter2):
        SeqIO.write([rec1,rec2], outfile, "fastq")
    outfile.close()

if __name__ == '__main__':
    outpath = "%s.merged.fastq" % os.path.splitext(sys.argv[1])[0]
    merge_fastq(sys.argv[1],sys.argv[2],outpath)

The neat trick is in line 13, using Python’s itertools to zip two iterators and loop over them in parallel two fastq records at a time.

How to use this script: download to a file you will call merge_fastq (or whatever). Then:

$ chmod +x merge_fastq

And you are ready to go.

$ ./merge_fastq myseq_1_.fastq myseq_2_.fastq

The merged file will be called myseq_1_.merged.fastq

I am learning a lot about scavenging tweets.  Apparently, I cannot go back beyond a few days using the api.search() function. Hence, if I try to search for all the #AFPCAFA11 hashtags I will get nothing from the meeting’s dates. But if I look for a user’s tweets using api.user_timeline() I can go back for months on the users timeline, and then filter out the tweets with the relevant hashtags.  Since it seems I was the principal twiterrer in that meeting, I’m putting up my tweets here. Apologies to the others who recorded the meeting using Twitter: if you want your tweets included, drop me a line with your Twitter user name.

Thu Jul 14 16:04:22 2011 At Vienna. #ISMB #AFPCAFA11 #ISMB11
Thu Jul 14 16:07:34 2011 At Vienna #ISMB #AFPCAFA11 Curious who is the best protein function predictor? Join us. http://bit.ly/htv3J7
Fri Jul 15 09:10:24 2011 Jesse Gillis from UBC on a function prediciton post-mortem #AFPCAFA11 #ISMB
Fri Jul 15 09:12:11 2011 This is going to be fun. Jesse Gillis UBC. Postmortem on MouseFunc #ISMB #AFPCAFA11 Precision / Recall of 0.06… argh.
Fri Jul 15 09:14:14 2011 http://bit.ly/obSISi MouseFunc experiment #AFPCAFA11 #ISMB
Fri Jul 15 09:28:58 2011 Multifunctionality affect prediction profoundly. Take-home message from Jesse Gillis’ talk #AFPCAFA11 #ISMB
Fri Jul 15 09:31:22 2011 Next up: Meghana Chitale from @kiharalab #ISMB #AFPCAFA11
Fri Jul 15 09:36:44 2011 Co-occurrence association scores. CAS Lookiong for associations across GOs: between a BPO term and a CCO term, for example. #AFPCAFA11
Fri Jul 15 09:41:17 2011 Missing enzyme predictions. My fav. Chtiale at #ISMB #AFPCAFA11
Fri Jul 15 09:56:08 2011 Yanay Ofran from Bar ilan U about multifunctionality. How to assess the number of false positives? #ISMB #AFPCAFA11
Fri Jul 15 09:56:44 2011 Prediciton of photosynthesis in an elephant genome is a good sign of false positives. Yanay #ISMB #AFPCAFA11
Fri Jul 15 10:02:56 2011 Precision of short motifs is surprisingly high. Yanay, #ISMB #AFPCAFA11
Fri Jul 15 10:05:42 2011 short motifs identify functional motifs. Whereas homology identifies evolutionary relatedness. #AFPCAFA11 #ISMB
Fri Jul 15 10:09:14 2011 Next up: me. #AFPCAFA11 #ISMB
Fri Jul 15 11:44:45 2011 David Jones from UCL is talking about his #AFPCAFA11 predictions. Many different features. #ISMB
Fri Jul 15 11:47:18 2011 profile-profile fold recognition works well in Function prediction as well. #AFPCAFA11 #ISMB
Fri Jul 15 11:53:02 2011 Jones talking about why it is unhealthy to exercise in the morning. #AFPCAFA11 #ISMB generation of free radicals. #excusesaregreat
Fri Jul 15 11:56:43 2011 49,000 features in an SVM. #ISMB #AFPCAFA11
Fri Jul 15 11:57:47 2011 Hard to believe no redundancy in 49K features…. #ISMB #AFPCAFA11
Fri Jul 15 11:59:17 2011 “I like this plot and I would make a t-shirt out of it, but in terms of scientific value its worth is zero”. Jones, #AFPCAFA11 #ISMB
Fri Jul 15 12:01:09 2011 New term heard for a 2nd time at #ISMB #AFPCAFA11 “postdiction” as opposed to “prediction”. #notsurewhatitmeans
Fri Jul 15 12:16:49 2011 Lightning talks at #AFPCAFA11 #ISMB starting now
Fri Jul 15 12:35:51 2011 Mary Jo Ondrechen on SALSA at #AFPCAFA11 #ISMB structure –&gt; function.
Fri Jul 15 12:36:45 2011 CDEHKRY make up 75% of all catalytic sites. Mary Jo #ISMB #AFPCAFA11
Fri Jul 15 12:50:50 2011 Jeffrey Yunes from UC Berkeley on SIFTER from Steven Brenner’s lab. #AFPCAFA11 #ISMB
Fri Jul 15 14:28:20 2011 Patrik Koskinen on a function prediction method called PANNZER. This will roll over well. #ISMB #AFPCAFA11
Fri Jul 15 14:30:30 2011 More information on PANNZER and the other methods at #AFPCAFA11 here: http://bit.ly/l9ayW9 #ISMB11
Fri Jul 15 14:33:16 2011 Koskinen mentioning Biothesaurus http://bit.ly/rnHdzp which removes errors due to synonyms #AFPCAFA11 #ISMB
Fri Jul 15 14:43:09 2011 Question: “How do you pronounce the name of that volcano that erupted in Iceland?” Answer: “I don’t”. Koskinen #AFPCAFA11 #ISMB
Fri Jul 15 14:50:27 2011 Olivier Lichtarge on using Evolutionary Trace Annotation (ETA) for function prediction. #AFPCAFA11 #ISMB
Fri Jul 15 14:51:12 2011 A network of protein structure networks. Memories of fragnostic. #AFPCAFA11 #ISMB
Fri Jul 15 14:52:49 2011 Using network diffusion to annotate protein structures. Lichtargee. #AFPCAFA11 #ISMB
Fri Jul 15 14:57:19 2011 compressing a clique to a star graph by adding a pseudo-node. Reduces problem from O(n^2) to O(n). Lichtarge #ISMB #AFPCAFA11
Fri Jul 15 15:09:17 2011 Amos Bairoch: of prosite, swissprot and expasy fame #AFPCAFA11 #ISMB
Fri Jul 15 15:12:51 2011 Due to alt-splicing and PTM 20,000 human genes –&gt; 5M different molecules! Bairoch #AFPCAFA11 #ISMB
Fri Jul 15 15:15:50 2011 Status codes of human protein function annotations: Maybe, potentially, putative, expected and hopefullly. Bairoch #ISMB #AFPCAFA11
Fri Jul 15 15:17:10 2011 &gt;100 GPCRs for which we do not know the ligand. Bairoch #ISMB #AFPCAFA11
Fri Jul 15 15:19:13 2011 Bairoch now talking about CALIPHO. 1)experimental verification of human protein function; 2)enable bioinformatics for same. #ISMB #AFPCAFA11
Fri Jul 15 15:20:44 2011 “How many ppl in this room have never used swissprot”. 0. #AFPCAFA11 #ISMB
Fri Jul 15 15:23:24 2011 Bairoch looks at small &lt;100aa intracellular protiens in experimental assays. #AFPCAFA11 #ISMB
Fri Jul 15 15:26:26 2011 Interesting proteins are expressed in olfactory pits of zebrafish. I didn’t know fish smell. #AFPCAFA11 #ISMB
Fri Jul 15 15:33:09 2011 If you get a new function, you cannot predict it, because of no ontology (yet). #AFPCAFA11 #ISMB
Sat Jul 16 06:58:43 2011 Predrag Radivojac explaining the vagaries of GO annotated databases #AFPCAFA11 #ISMB
Sat Jul 16 06:59:48 2011 Assessment of protein function prediction methods going on now in Hall L #ISMB #AFPCAFA11
Sat Jul 16 07:04:08 2011 Radivojac: “It’s possible to achieve a precision of 1, it just won’t happen”. #AFPCAFA11 #ISMB
Sat Jul 16 07:29:50 2011 Assessment of protein function prediction methods going on now in Hall L #ISMB #AFPCAFA11 http://bit.ly/htv3J7 Sean Mooney is up.
Sat Jul 16 08:05:49 2011 Christine Orengo on her team’s work at #AFPCAFA11
Sat Jul 16 08:06:28 2011 Orengo says that they are not really function predictors, but evolutionary classifiers #AFPCAFA11 #ISMB
Sat Jul 16 09:18:03 2011 Shaneka Simmon from Jackson State on predicting functions associated with biofeuls – universal stress protein domains. #AFPCAFA11 #ISMB
Sat Jul 16 09:21:30 2011 Simmons: look for diversity of universal stress response genes. in Rhodopseudomonas palustris. #AFPCAFA11 #ISMB11
Sat Jul 16 11:33:52 2011 http://yfrog.com/kevdmbqj #AFPCAFA11 #ismb discussion panel now
Sat Jul 16 14:46:07 2011 Wyatt shows that paralogs actually give better annotation transfer than orthologs. http://bit.ly/nWShuB #AFPCAFA11 #ISMB
Sat Jul 16 14:47:17 2011 Wyatt’s claim runs contrary to common wisdom. Which is good http://bit.ly/nWShuB #AFPCAFA11 #ISMB
Thu Jul 21 22:42:34 2011 After all the talk about standards at #AFPCAFA11 #ISMB this is very timely: http://xkcd.com/927/

I will put the code for the application up later.  (Temporary name: Vulture.)

Fri Jul 22 21:00:20 2011 pjacock #BOSC2011 (pre #ISMB SIG) notes by @chapmanb – Day Two pm: #Semantic Web session, and misc #opensource project session http://t.co/TDjmx6B
Fri Jul 22 20:58:53 2011 pjacock #BOSC2011 (pre #ISMB SIG) notes by @chapmanb – Day Two am: Amazon’s Matt Wood @mza keynote, #cloud computing session http://t.co/BaiOz5W
Fri Jul 22 20:55:41 2011 pjacock #BOSC2011 (pre #ISMB SIG) notes by @chapmanb – Day One pm: Visualization &amp; #NGS sessions http://t.co/JuvLrex
Fri Jul 22 20:54:45 2011 pjacock #BOSC2011 (pre #ISMB SIG) notes by @chapmanb – Day One am: Larry Hunter’s keynote, and Genome Content Management session http://t.co/gfdJLv7
Fri Jul 22 20:48:57 2011 pjacock MT @GeneWikiPulse bio-ontologies 2011 – ontologies need lexicons: I recently returned from my first #ISMB in Vienna, … http://t.co/kMCNaxh
Fri Jul 22 20:09:38 2011 suganthibala RT @keesvanbochove: Closing remark of Michael Ashburner, a godfather of #bioinformatics, at #ismb: don’t be proprietary about your research, be open.
Fri Jul 22 17:59:59 2011 YiliangDing RT @GenomeBiology: Ana Conesa: Seq depth affects the relative proportions of RNA classes in RNA-seq datasets #ISMB #genomics
Fri Jul 22 14:20:50 2011 BioCatalogue RT @fiedawn: #ismb #biosharing Carole Goble – we have a lot of descriptions in the BioCatalogue – how can we mark up/export to bioDBCore? underway
Fri Jul 22 13:25:30 2011 razoralign RT @GenomeBiology: Read Genome Biology’s take on ISMB 2011 on the BMC blog http://t.co/dmuhQ7J #genomics #ISMB
Fri Jul 22 11:52:01 2011 druvus RT @keesvanbochove: Good shows how they linked SNPedia with Gene Wiki articles using Semantic MediaWiki. Almost no overlap of gene-disease rels in wikis!! #ismb
Fri Jul 22 11:50:41 2011 druvus RT @_lrr_: Simple yet very handy tool: fastapl (http://bit.ly/rhkKCl), had a poster at #ismb
Fri Jul 22 11:43:00 2011 coding_doc RT @GenomeBiology: Read Genome Biology’s take on ISMB 2011 on the BMC blog http://t.co/dmuhQ7J #genomics #ISMB
Fri Jul 22 09:07:58 2011 jackwillstone RT @GenomeBiology: Read Genome Biology’s take on ISMB 2011 on the BMC blog http://t.co/dmuhQ7J #genomics #ISMB
Fri Jul 22 09:00:55 2011 raunakms RT @GenomeBiology: Read Genome Biology’s take on ISMB 2011 on the BMC blog http://t.co/dmuhQ7J #genomics #ISMB
Fri Jul 22 09:00:46 2011 GenomeMedicine RT @GenomeBiology: Read Genome Biology’s take on ISMB 2011 on the BMC blog http://t.co/dmuhQ7J #genomics #ISMB
Fri Jul 22 09:00:31 2011 BioMedCentral RT @GenomeBiology: Read Genome Biology’s take on ISMB 2011 on the BMC blog http://t.co/dmuhQ7J #genomics #ISMB
Fri Jul 22 07:48:42 2011 sharmanedit RT @GenomeBiology Read Genome Biology’s take on ISMB 2011 on the BMC blog http://t.co/dmuhQ7J #genomics #ISMB
Fri Jul 22 01:08:29 2011 SemanticMW RT @keesvanbochove: Good shows how they linked SNPedia with Gene Wiki articles using Semantic MediaWiki. Almost no overlap of gene-disease rels in wikis!! #ismb
Thu Jul 21 22:42:34 2011 iddux After all the talk about standards at #AFPCAFA11 #ISMB this is very timely: http://xkcd.com/927/
Thu Jul 21 19:30:33 2011 druvus RT @GenomeBiology: Read Genome Biology’s take on ISMB 2011 on the BMC blog http://t.co/dmuhQ7J #genomics #ISMB
Thu Jul 21 17:10:44 2011 GenomeBiology Read Genome Biology’s take on ISMB 2011 on the BMC blog http://t.co/dmuhQ7J #genomics #ISMB
Thu Jul 21 15:01:18 2011 bffo on way home 2 YYZ, leaving FRA on @aircanada, ~2 weeks on road. VIE for #ISMB and Kyoto (via KIX) 4 #ICGC. on plane feels like we r home
Thu Jul 21 13:54:11 2011 pjacock To all those who thanked me for #bosc2011 / #ISMB / #eccb2011 (live) tweets, no problem – it was an interesting experiment in note taking.
Thu Jul 21 12:36:39 2011 _lrr_ Simple yet very handy tool: fastapl (http://bit.ly/rhkKCl), had a poster at #ismb
Thu Jul 21 10:55:34 2011 druvus RT @dullhunk: Are videos of the #ISMB keynotes by Ashburner, Berger, Thornton, Serrano, Troyanskaya and Valencia online anywhere? #bioinformatics
Thu Jul 21 10:54:17 2011 druvus RT @GigaScience: Another applied example of #usegalaxy from Marc Bras, with a pipeline for SNP detection in the grapevine: MAPHiTS http://t.co/yVQ3POt #ISMB
Thu Jul 21 10:44:54 2011 bffo MT @GigaScience: #ISMB write-up in GigaBlog: Final impressions of Vienna: time 2 go w/t (work)flow… http://bit.ly/r6JaN7 #bioinformatics
Thu Jul 21 08:49:27 2011 fredebibs RT @druvus: ISMB/ECCB 2011 proceedings papers are online http://t.co/CkERlvb #ismb
Thu Jul 21 08:01:27 2011 iainh_z RT @GigaScience: Another #ISMB write-up in GigaBlog: Final impressions of Vienna: time to go with the (work)flow… http://t.co/ZVluBMa
Thu Jul 21 05:49:15 2011 heikkil RT @GigaScience: Another applied example of #usegalaxy from Marc Bras, with a pipeline for SNP detection in the grapevine: MAPHiTS http://t.co/yVQ3POt #ISMB
Thu Jul 21 03:47:52 2011 galaxyproject RT @GigaScience: Another applied example of #usegalaxy from Marc Bras, with a pipeline for SNP detection in the grapevine: MAPHiTS http://t.co/yVQ3POt #ISMB
Thu Jul 21 03:45:10 2011 galaxyproject RT @GigaScience: Another #ISMB write-up in GigaBlog: Final impressions of Vienna: time to go with the (work)flow… http://t.co/ZVluBMa
Thu Jul 21 02:43:42 2011 terryogara From chaos, beauty. RT @iGenomics: RW: Rather to fight noise, use noise to make a robust system. Add an oscillator to the system. #ismb
Wed Jul 20 22:03:00 2011 chlalanne RT @druvus: ISMB/ECCB 2011 proceedings papers are online http://t.co/CkERlvb #ismb
Wed Jul 20 21:30:05 2011 jxtx RT @GigaScience: Another #ISMB write-up in GigaBlog: Final impressions of Vienna: time to go with the (work)flow… http://t.co/ZVluBMa
Wed Jul 20 21:25:48 2011 GigaScience Another #ISMB write-up in GigaBlog: Final impressions of Vienna: time to go with the (work)flow… http://t.co/ZVluBMa
Wed Jul 20 20:47:27 2011 aadhyadi RT @ianholmes: &quot;Don’t be afraid to work with people smarter than you. And work with people you like.&quot; Michael Ashburner, closing keynote, #ismb 2011
Wed Jul 20 20:40:34 2011 druvus ISMB/ECCB 2011 proceedings papers are online http://t.co/CkERlvb #ismb
Wed Jul 20 20:23:34 2011 olgabot @nerdgirls #ismb #ECCB11 was fantastic! Gained deep knowledge in my field, learned about new developments, and made some great friends
Wed Jul 20 20:23:19 2011 _lrr_ RT @RishaNarayan: Really enjoyed the ISMB/ECCB 2011 conference. Many thanks to the organisers. #ismb
Wed Jul 20 20:15:09 2011 lopantano RT @ianholmes: In closing #ismb keynote, Mike Ashburner quoted English philosopher(?) &quot;Science is public knowledge. If it is not open, it is not science.&quot;
Wed Jul 20 19:59:57 2011 _lrr_ Had a great party at flex.at! RT @SaggiSardar: ISMB over for another year. Great conference. Now it’s time to enjoy Vienna! #ISMB
Wed Jul 20 18:39:15 2011 NatureRevGenet Congrats due to all the #ismb speakers for invariably clear and engaging talks
Wed Jul 20 16:46:36 2011 yeastgenome RT @bffo:Cherry,Ashburner and Blake; Sc, Dm &amp; Mm, at the beginning of GO #ISMB http://yfrog.com/kl70850759j indeed a great closing lecture
Wed Jul 20 16:37:08 2011 dullhunk Are videos of the #ISMB keynotes by Ashburner, Berger, Thornton, Serrano, Troyanskaya and Valencia online anywhere? #bioinformatics
Wed Jul 20 16:00:19 2011 bffo Cherry, Ashburner and Blake; Sc, Dm &amp; Mm, at the beginning of GO #ISMB http://yfrog.com/kl70850759j indeed a great closing lecture
Wed Jul 20 14:12:39 2011 tsucheta RT @pjacock: Michael Ashburner #ISMB tells young scientists to be open in their work. If knowledge is not open, it is not science! #openaccess #opendata
Wed Jul 20 14:00:21 2011 tsucheta RT @ianholmes: &quot;Don’t be afraid to work with people smarter than you. And work with people you like.&quot; Michael Ashburner, closing keynote, #ismb 2011
Wed Jul 20 13:49:25 2011 avilella RT @ianholmes: Mike Ashburner claims &quot;I never had to look for a job, and I’ve never been short of funding&quot;. Apparently 1970′s UK = science paradise #ismb
Wed Jul 20 12:52:39 2011 cbjones1943 RT @ianholmes: Once again I recommend Ashburner’s book &quot;Won for All&quot; for more such dirt-dishing details of millenial genomics http://t.co/otaIgvZ #ismb
Wed Jul 20 12:46:58 2011 genomeresearch RT @ianholmes: Once again I recommend Ashburner’s book &quot;Won for All&quot; for more such dirt-dishing details of millenial genomics http://t.co/otaIgvZ #ismb
Wed Jul 20 12:45:48 2011 cshperspectives Ashburner: Gerry Rubin &quot;to his credit&quot; recognized the merit of Venter’s approach but &quot;Venter nearly screwed us&quot; #ismb via @ianholmes
Wed Jul 20 12:21:24 2011 coding_doc RT @ianholmes: In closing #ismb keynote, Mike Ashburner quoted English philosopher(?) &quot;Science is public knowledge. If it is not open, it is not science.&quot;
Wed Jul 20 12:17:39 2011 gthorisson Cannot believe my luck: flight from #ismb Vienna landed at Heathrhrow 25min early, so able to catch early bus to Oxford to meet colleagues
Wed Jul 20 11:47:34 2011 ClaireAinsworth RT @dgmacarthur: Check out @ianholmes for highlights of what sounds like a brilliant closing #ISMB keynote by Michael Ashburner.
Wed Jul 20 11:44:55 2011 sharmanedit RT @ianholmes: Once again I recommend Ashburner’s book &quot;Won for All&quot; for more such dirt-dishing details of millenial genomics http://t.co/otaIgvZ #ismb
Wed Jul 20 11:43:29 2011 sharmanedit Follow @ianholmes now for great live tweeting of Michael Ashburner’s fascinating closing keynote at #ismb 2011
Wed Jul 20 11:30:14 2011 ianholmes Once again I recommend Ashburner’s book &quot;Won for All&quot; for more such dirt-dishing details of millenial genomics http://t.co/otaIgvZ #ismb
Wed Jul 20 11:28:56 2011 ianholmes Ashburner gave credit to Suzi Lewis for the idea of 1999 Drosophila annotation jamboree &amp; to Celera for funding it: &quot;cheap consulting&quot; #ismb
Wed Jul 20 11:27:59 2011 17thescorpion RT @iGenomics: Michael Ashburner: Try to work with people who are smarter than you are. #ismb
Wed Jul 20 11:27:20 2011 KatherineMejia RT @ianholmes: &quot;Don’t be afraid to work with people smarter than you. And work with people you like.&quot; Michael Ashburner, closing keynote, #ismb 2011
Wed Jul 20 11:27:18 2011 ianholmes Ashburner’s early sequencing stories: getting Nature paper for ~5kb of fly DNA. Being scooped after talking about a gene to competitor #ismb
Wed Jul 20 11:24:58 2011 ianholmes Ashburner never intended to go into compbio. Even genetics was an accident. Recounted early adventures w/Phoenix, Vax, ARPAnet, gopher #ismb
Wed Jul 20 11:19:50 2011 dgmacarthur Check out @ianholmes for highlights of what sounds like a brilliant closing #ISMB keynote by Michael Ashburner.
Wed Jul 20 11:19:06 2011 gilbertjacka RT @ianholmes: Mike Ashburner claims &quot;I never had to look for a job, and I’ve never been short of funding&quot;. Apparently 1970′s UK = science paradise #ismb
Wed Jul 20 11:18:10 2011 ianholmes Mike Ashburner claims &quot;I never had to look for a job, and I’ve never been short of funding&quot;. Apparently 1970′s UK = science paradise #ismb
Wed Jul 20 11:17:08 2011 gawbul RT @ianholmes: Mike Ashburner noted that his own hacker, Aubrey de Grey, achieved &quot;later notoriety as a gerontologist&quot; #ismb
Wed Jul 20 11:16:10 2011 systemsbiology RT @ianholmes: Mike Ashburner turned down by Cambridge..for undergrad deg; took pleasure in turning down Zoology Dept chair 20yrs on #ismb
Wed Jul 20 11:15:23 2011 gawbul RT @ianholmes: Ashburner said Drosophila was his second love affair #ismb
Wed Jul 20 11:15:14 2011 gawbul RT @ianholmes: Ashburner accepted to do Genetics degree at Cambridge. Got married, learned genetics in a Naples lab that summer. Came back did degree #ismb
Wed Jul 20 11:14:05 2011 gawbul RT @ianholmes: Mike Ashburner was turned down by Cambridge Zoology for undergrad degree; took pleasure in turning down Zoology Dept chair 20yrs on #ismb
Wed Jul 20 11:12:58 2011 gawbul RT @ianholmes: In talking about Gene Ontology, Ashburner praised co-founders, as well as Barry Smith: &quot;initially annoying&quot; but &quot;a true philosopher&quot; #ismb
Wed Jul 20 11:12:54 2011 gawbul RT @ianholmes: &quot;Don’t be afraid to work with people smarter than you. And work with people you like.&quot; Michael Ashburner, closing keynote, #ismb 2011
Wed Jul 20 11:12:51 2011 ianholmes Mike Ashburner noted that his own hacker, Aubrey de Grey, achieved &quot;later notoriety as a gerontologist&quot; #ismb
Wed Jul 20 11:12:27 2011 gawbul RT @ianholmes: In closing #ismb keynote, Mike Ashburner quoted English philosopher(?) &quot;Science is public knowledge. If it is not open, it is not science.&quot;
Wed Jul 20 11:11:51 2011 ianholmes Ashburner’s #ismb pioneers: Roger Staden (Fred Sanger’s hacker), Doug Brutlag (Stanford compbio archive), Amos Bairoch (1st bio webserver)
Wed Jul 20 11:07:57 2011 ianholmes &quot;Barry Smith – you either love him or you hate him&quot; – Michael Ashburner, closing keynote, #ismb 2011
Wed Jul 20 11:06:55 2011 ianholmes &quot;Don’t be afraid to work with people smarter than you. And work with people you like.&quot; Michael Ashburner, closing keynote, #ismb 2011
Wed Jul 20 11:05:44 2011 ianholmes In talking about Gene Ontology, Ashburner praised co-founders, as well as Barry Smith: &quot;initially annoying&quot; but &quot;a true philosopher&quot; #ismb
Wed Jul 20 11:04:44 2011 ilpuccio Reordering ideas after #BOSC2011 and #ISMB
Wed Jul 20 11:03:30 2011 ianholmes Ashburner clearly enjoyed his time at CalTech (think this was postdoc?) and mentioned Feynman – wonder if they met #ismb
Wed Jul 20 11:01:51 2011 ianholmes Ashburner said Drosophila was his second love affair #ismb
Wed Jul 20 11:01:27 2011 ianholmes Ashburner accepted to do Genetics degree at Cambridge. Got married, learned genetics in a Naples lab that summer. Came back did degree #ismb
Wed Jul 20 10:59:57 2011 ianholmes When Ashburner first invited to CalTech &quot;I thought in my ignorance, why go to an Institute of Tech? Didn’t realize home of Drosophila&quot; #ismb
Wed Jul 20 10:58:42 2011 ianholmes Gerry Rubin &quot;to his great credit&quot; recognized merit of Craig Venter’s approach to sequencing. But &quot;Venter nearly screwed us&quot; -Ashburner #ismb
Wed Jul 20 10:56:57 2011 ianholmes Mike Ashburner was turned down by Cambridge Zoology for undergrad degree; took pleasure in turning down Zoology Dept chair 20yrs on #ismb
Wed Jul 20 10:56:18 2011 wimufi RT @ianholmes: In closing #ismb keynote, Mike Ashburner quoted English philosopher(?) &quot;Science is public knowledge. If it is not open, it is not science.&quot;
Wed Jul 20 10:53:13 2011 ianholmes Mike Ashburner’s #ismb keynote concluded with &quot;lessons&quot;. It’s all about luck. But must exploit that luck. Get a guru/mentor/parent. Be open.
Wed Jul 20 10:51:18 2011 ianholmes In fine (blissfully un-PC) form, Mike Ashburner also relished stories of competition with &quot;the Germans&quot;, &quot;the Spanish&quot; etc. #ismb
Wed Jul 20 10:50:23 2011 ianholmes Ashburner also noted (and NB I’m not endorsing every quote! but his #ismb keynote WAS juicy) that he’d never be an American citizen.
Wed Jul 20 10:49:05 2011 ianholmes Mike Ashburner was offered a UK biowar job out of college, but refused. Wonders now if he would’ve got security clearance. Hopes not. #ismb
Wed Jul 20 10:47:53 2011 ianholmes In closing #ismb keynote, Mike Ashburner quoted English philosopher(?) &quot;Science is public knowledge. If it is not open, it is not science.&quot;
Wed Jul 20 10:45:13 2011 ianholmes To say Gene Ontology received coolly at #ismb Halkidiki in ’97 an understatement; Ashburner &quot;almost laughed out of room&quot; by Sander, Durbin
Wed Jul 20 10:43:23 2011 ianholmes I highly recommend Ashburner’s book &quot;Won for All&quot;. Candid autobiography of the millenial corporate genome wars http://t.co/otaIgvZ #ismb #fb
Wed Jul 20 10:43:10 2011 druvus I have enjoyed following #ismb tweets from my sunny garden
Wed Jul 20 10:40:34 2011 ianholmes I *really* enjoyed Michael Ashburner’s closing #ISMB keynote. I was unable to tweet at the time but will record some highlights.
Wed Jul 20 10:40:11 2011 ianholmes Nice –&gt; @nutrigenomics @iGenomics Ron Weiss: Don’t fight noise; use it to make gene circuits robust. Add an oscillator to the system. #ismb
Wed Jul 20 10:33:54 2011 ianholmes RT @iGenomics: Michael Ashburner: Try to work with people who are smarter than you are. #ismb
Wed Jul 20 10:33:51 2011 ianholmes RT @iGenomics: Michael Ashburner: Science is public knowledge. If it is not open, it is not science. #ismb
Wed Jul 20 08:59:25 2011 samuellampa RT @iGenomics: A Bioinformatics training resource: http://www.biotnet.org/ #ismb
Wed Jul 20 08:37:30 2011 biomol_info RT @iGenomics: A Bioinformatics training resource: http://www.biotnet.org/ #ismb
Wed Jul 20 08:25:30 2011 gthorisson On my way home from #ISMB. Vienna airport is crowded, stuffy and not very pleasant. But, it has free wireless Internet so it ROX.
Wed Jul 20 06:56:48 2011 bffo block dates for #ISMB next year (and surrounding dates for SIGs): July 15-17 2012 , this year was great, c u all in LA next year!
Wed Jul 20 06:28:06 2011 iliasSkalk RT @iGenomics: Michael Ashburner: Try to work with people who are smarter than you are. #ismb
Wed Jul 20 06:27:46 2011 iliasSkalk RT @iGenomics: Michael Ashburner: Science is public knowledge. If it is not open, it is not science. #ismb
Wed Jul 20 01:33:31 2011 yeastgenome RT @gthorisson: Fantastic #ISMB keynote from Michael Ashburner. What an inspiration. Key msgs: ‘collaborate with people brighter than you’ and ‘openness’
Wed Jul 20 01:32:27 2011 yeastgenome RT @pjacock: Michael Ashburner #ISMB tells young scientists to be open in their work. If knowledge is not open, it is not science! #openaccess #opendata
Wed Jul 20 00:00:26 2011 robymuhamad RT @timjph: @iGenomics here’s report I mentioned: 3.8b$ on human genome project; 310k jobs created &amp; ~800b$ economic impact http://j.mp/rbXSbk #ismb
Tue Jul 19 23:53:57 2011 robaganrab RT @iGenomics: Michael Ashburner: Chance happens in life. You have to exploit it #ismb
Tue Jul 19 23:38:41 2011 scroeser RT @_lrr_: Michael Ashburner: &quot;If knowledge is not public it is not science. Period.&quot; #ismb #eccb11 #openscience
Tue Jul 19 22:53:00 2011 ematsen RT @iddux: HumanN, a new metagenomic analysis package from Huttenhower http://j.mp/pHkWhk #ISMB
Tue Jul 19 22:36:32 2011 SaggiSardar ISMB over for another year. Great conference. Now it’s time to enjoy Vienna! #ISMB
Tue Jul 19 22:30:06 2011 aaronquinlan RT @iGenomics: Michael Ashburner: Follow Syndey Brenner, he will not use slides because a good phrase is worth thousand of Powerpoint slides. #ismb
Tue Jul 19 21:09:21 2011 aadhyadi RT @iGenomics: Michael Ashburner: Try to work with people who are smarter than you are. #ismb
Tue Jul 19 21:09:00 2011 chofski RT @SUPERFAMILY: Congratulations to Adam Sarder on winning the outstanding poster award at #ISMB (it’s poster F22 if you want to see it!)
Tue Jul 19 20:42:57 2011 wspoonr RT @pjacock: Ashburner #ISMB tells young scientists to be open in their work. If knowledge is not open, it is not science! #openscience
Tue Jul 19 19:36:10 2011 simon_andrews After all of the #ISMB delegates have left, our hotel wifi mysteriously starts working again.
Tue Jul 19 19:14:33 2011 KamounLab RT @pjacock: Michael Ashburner #ISMB tells young scientists to be open in their work. If knowledge is not open, it is not science! #openaccess #opendata
Tue Jul 19 19:14:24 2011 KamounLab RT @iGenomics: Michael Ashburner: Try to work with people who are smarter than you are. #ismb
Tue Jul 19 18:57:14 2011 julientap RT @iddux: HumanN, a new metagenomic analysis package from Huttenhower http://j.mp/pHkWhk #ISMB
Tue Jul 19 18:49:04 2011 alalejandro RT @iGenomics: Michael Ashburner: Science is public knowledge. If it is not open, it is not science. #ismb
Tue Jul 19 18:48:56 2011 alalejandro RT @gthorisson: Fantastic #ISMB keynote from Michael Ashburner. What an inspiration. Key msgs: ‘collaborate with people brighter than you’ and ‘openness’
Tue Jul 19 18:48:07 2011 alalejandro If only people would understand how essential this is! MT @keesvanbochove Ashburner #ismb: don’t be proprietary abt your research, be open.
Tue Jul 19 18:46:17 2011 RishaNarayan Really enjoyed the ISMB/ECCB 2011 conference. Many thanks to the organisers. #ismb
Tue Jul 19 18:42:56 2011 caseybergman RT @gthorisson: Fantastic #ISMB keynote from Michael Ashburner. What an inspiration. Key msgs: ‘collaborate with people brighter than you’ and ‘openness’
Tue Jul 19 18:40:34 2011 bergmanlab RT @olgabot: #ismb &quot;If knowledge is not public it is not science&quot; – Michael Ashburner
Tue Jul 19 18:40:33 2011 caseybergman RT @olgabot: #ismb &quot;If knowledge is not public it is not science&quot; – Michael Ashburner
Tue Jul 19 18:31:02 2011 iddux HumanN, a new metagenomic analysis package from Huttenhower http://j.mp/pHkWhk #ISMB
Tue Jul 19 18:19:10 2011 iddux @_lrr_: @fionabrinkman learned at #ismb that what we call &quot;analogs&quot; today used to be called &quot;orthologs&quot; by 1s… (cont) http://deck.ly/~yFYyV
Tue Jul 19 18:18:07 2011 iddux @_lrr_: @fionabrinkman learned at #ismb that what we call &quot;orthologs&quot; today used to be called &quot;analogs&quot; by 1st evolutionary scientists.
Tue Jul 19 17:27:04 2011 4a6a5a RT @simon_andrews: 2 people have now confused me with Simon Anders (DeSeq etc) I should learn more about RNASeq to be able to bluff better. #ismb
Tue Jul 19 17:24:43 2011 Accelrys RT @Fabio11211 #ISMB conf draws to an end! Strong presence &amp; interest at Accelrys booth for NextGenSeq &amp; Protein Modelling solutions
Tue Jul 19 17:19:48 2011 Chris_Evelo MT @pjacock: Gary Bader suggested http://bit.ly/mPS9LS for shared #bioinformatics tutorials, eg has introduction Cytoscape #ISMB Workshop
Tue Jul 19 17:17:55 2011 suknamgoong RT @iGenomics: Michael Ashburner: Try to work with people who are smarter than you are. #ismb
Tue Jul 19 17:16:43 2011 cytoscape RT @pjacock: Gary Bader suggested http://t.co/jNFVbjr as one project to shared #bioinformatics tutorials, eg has introduction Cytoscape #ISMB Workshop
Tue Jul 19 17:02:34 2011 BetaScience @bgood Wish I was at #ismb with you. I have some great memories from that conference and #Vienna. #pre-kids
Tue Jul 19 16:55:50 2011 betsyrolland RT @pjacock: Michael Ashburner #ISMB tells young scientists to be open in their work. If knowledge is not open, it is not science! #openaccess #opendata
Tue Jul 19 16:50:41 2011 jpatanooga RT @keesvanbochove: Closing remark of Michael Ashburner, a godfather of #bioinformatics, at #ismb: don’t be proprietary about your research, be open.
Tue Jul 19 16:22:44 2011 gailfdavies RT @olgabot: #ismb &quot;If knowledge is not public it is not science&quot; – Michael Ashburner
Tue Jul 19 16:20:55 2011 iGenomics @westr Yes, indeed. Michael Ashburner borrowed it to tell 3 life lessons. #ismb
Tue Jul 19 16:18:38 2011 pierrepo RT @gthorisson: Fantastic #ISMB keynote from Michael Ashburner. What an inspiration. Key msgs: ‘collaborate with people brighter than you’ and ‘openness’
Tue Jul 19 16:12:37 2011 FigShare RT @olgabot: #ismb &quot;If knowledge is not public it is not science&quot; – Michael Ashburner
Tue Jul 19 16:12:19 2011 tweetruth RT @pjacock: Michael Ashburner #ISMB tells young scientists to be open in their work. If knowledge is not open, it is not science! #openaccess #opendata
Tue Jul 19 16:11:49 2011 FigShare RT @keesvanbochove: Closing remark of Michael Ashburner, a godfather of #bioinformatics, at #ismb: don’t be proprietary about your research, be open.
Tue Jul 19 16:11:22 2011 kshameer RT @antidemagogue: MA: Knowledge which is not public is not science, period. #ismb #bioinformatics #genomics
Tue Jul 19 16:11:08 2011 iscbsc for those student in Vienna, at 8 at stephanplatz #scs2011 #ISMB
Tue Jul 19 16:11:04 2011 kshameer RT @keesvanbochove: Closing remark of Michael Ashburner, a godfather of #bioinformatics, at #ismb: don’t be proprietary about your research, be open.
Tue Jul 19 16:04:14 2011 c_rdzl RT @iGenomics: Michael Ashburner: Science is public knowledge. If it is not open, it is not science. #ismb
Tue Jul 19 16:03:00 2011 ffalconi RT @iGenomics: Michael Ashburner: Chance happens in life. You have to exploit it #ismb
Tue Jul 19 16:01:34 2011 science3point0 RT @pjacock: Michael Ashburner #ISMB tells young scientists to be open in their work. If knowledge is not open, it is not science! #openaccess #opendata
Tue Jul 19 16:01:01 2011 GigaScience RT @pjacock: Michael Ashburner #ISMB tells young scientists to be open in their work. If knowledge is not open, it is not science! #openaccess #opendata
Tue Jul 19 15:59:27 2011 pjacock For 2012, #ISMB in Long Beach, USA, and #ECCB in Basel, Switzerland
Tue Jul 19 15:59:21 2011 keesvanbochove RT @timjph: @iGenomics here’s report I mentioned: 3.8b$ on human genome project; 310k jobs created &amp; ~800b$ economic impact http://j.mp/rbXSbk #ismb
Tue Jul 19 15:59:20 2011 fredebibs RT @gthorisson: Fantastic #ISMB keynote from Michael Ashburner. What an inspiration. Key msgs: ‘collaborate with people brighter than you’ and ‘openness’
Tue Jul 19 15:55:20 2011 pjacock RT @gthorisson: Fantastic #ISMB keynote from Michael Ashburner. What an inspiration. Key msgs: ‘collaborate with people brighter than you’ and ‘openness’
Tue Jul 19 15:54:42 2011 keesvanbochove Closing remark of Michael Ashburner, a godfather of #bioinformatics, at #ismb: don’t be proprietary about your research, be open.
Tue Jul 19 15:54:34 2011 pjacock Embarrassingly many of the #ISMB / #eccb2011 prize winners haven’t stayed for the prize announcements in the closing session
Tue Jul 19 15:52:34 2011 _lrr_ Michael Ashburner: &quot;If knowledge is not public it is not science. Period.&quot; #ismb #eccb11 #openscience
Tue Jul 19 15:52:31 2011 gthorisson RT @antidemagogue: MA: Knowledge which is not public is not science, period. #ismb
Tue Jul 19 15:52:26 2011 ajordens RT @iGenomics: Michael Ashburner: Try to work with people who are smarter than you are. #ismb
Tue Jul 19 15:51:54 2011 gthorisson Fantastic #ISMB keynote from Michael Ashburner. What an inspiration. Key msgs: ‘collaborate with people brighter than you’ and ‘openness’
Tue Jul 19 15:49:33 2011 pjacock RT @iGenomics: Michael Ashburner: Chance happens in life. You have to exploit it #ismb
Tue Jul 19 15:49:30 2011 pjacock RT @iGenomics: Michael Ashburner: Try to work with people who are smarter than you are. #ismb
Tue Jul 19 15:48:53 2011 pjacock #ISMB #killerapp award goes to Syed Asad Rahman for EC-BLAST which searches for similar enzymes based on chemical knowledge
Tue Jul 19 15:48:08 2011 antidemagogue MA: Knowledge which is not public is not science, period. #ismb
Tue Jul 19 15:48:02 2011 iGenomics Michael Ashburner: Chance happens in life. You have to exploit it #ismb
Tue Jul 19 15:46:51 2011 pjacock RT @iGenomics: Michael Ashburner: Science is public knowledge. If it is not open, it is not science. #ismb
Tue Jul 19 15:46:35 2011 druvus RT @pjacock: Michael Ashburner #ISMB tells young scientists to be open in their work. If knowledge is not open, it is not science! #openaccess #opendata
Tue Jul 19 15:46:34 2011 antidemagogue MA: Exploit your luck. Collaborate. Communicate research openly. #ismb
Tue Jul 19 15:46:21 2011 iGenomics Michael Ashburner: Try to work with people who are smarter than you are. #ismb
Tue Jul 19 15:45:45 2011 pjacock Michael Ashburner #ISMB tells young scientists to be open in their work. If knowledge is not open, it is not science! #openaccess #opendata
Tue Jul 19 15:45:37 2011 olgabot #ismb &quot;If knowledge is not public it is not science&quot; – Michael Ashburner
Tue Jul 19 15:45:17 2011 iGenomics Michael Ashburner: Science is public knowledge. If it is not open, it is not science. #ismb
Tue Jul 19 15:44:55 2011 biobrichter #ISMB ashburner talk. informative, brings back the memories of the seq 90′s, but very ashburner-centric. True:collab with brighter people!
Tue Jul 19 15:44:26 2011 pjacock Michael Ashburner wrapping up his #ISMB keynote, describes career as a random walk. Recommends collaborating with people brighter than you!
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