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International Conference on Intelligent Systems for Molecular Biology
The talk specific feeds will be created each day shortly before the start of the first presentation. Find talk specific blogs by searching here for the title of the talk or the talk identifier as given in the program (like HL03 for the 3rd Highlight paper). The feeds can also be accessed on the conference pages in the according sections: SIGs, Keynotes, LBR, Proceedings, Tech Track and Highlights.

Happy blogging !!
HL31: Sujay Chattopadhyay - Selection for hotspot mutations in core genes of Escherichia coli
HL29: Tandy Warnow - Fast and accurate large-scale co-estimation of alignments and trees
PT33: Adam Richards - Assessing the functional coherence of gene sets with metrics based on the Gene Ontology graph
Visit the ISMB/ECCB 2011 Live Blog:
HL01: Sriram Sankararaman - Genomic privacy and limits of individual detection in a pool
3Dsig: Structural Bioinformatics & Computational Biophysics Satellite Meeting
LBR09: Peter Van Loo - Allele-specific copy number analysis of breast carcinomas
PT48: Tao Peng - Quantifying the distribution of probes between subcellular locations using unsupervised pattern unmixing
Ruchira S. Datta
Thanks so much for the coverage today!
I happily join in this shoulder clapping reverence to your group's important contribution to the success of this meeting. What else could ISCB do to support your efforts? - Burkhard Rost
How about some form of travel award, or registration discount? It might be conditioned on some minimum microblogging metric (carefully designed to avoid perverse incentives). - Ruchira S. Datta
LBR22: Nitesh Chawla - Exploring Disease Interactions Using Combined Gene and Phenotype Networks
PT05: Mitul Saha - MOTIF-EM: an Automated Computational Tool for Identifying Conserved Regions in CryoEM Structures
Nice tool - arne
3D SIFT descriptors are used for comparison of EM density maps - Dina Schneidman
LBR11: Mark Wass - Towards the prediction of protein interaction partners using physical docking
1-10% of protein-protein interactions have been identified. Need for prediction. - Roland Krause
Most methods for prediction are genomic or sequence based but not structure based. - Roland Krause
Protein docking: finding and scoring interaction poses between two proteins. Hard problem to distinguish interactors from non-interactors. Use of the Weng benchmark set of 65 complexes. Measure distribution of scores. - Roland Krause
Build decoy set and assume they are not interacting with the benchmark set. Some examples show separation but fails for several. 36 complexes outperform rank better than the 80%. - Roland Krause
Where on the interactors are docking solutions generated? Some AA are involved more frequently than others. - Roland Krause
Still way to go before predictions are possible but a signal is present. - Roland Krause
The problem with methods that try to optimize discrimination between natives and a set of decoys is that they usually find problems in the docking software / energy function. I.e. you'll discover that decoys have very weird electrostatics distribution etc... A good set of non-interactors would be key to develop this field further - Nir London
scoring is indeed a bottleneck in docking. however there is a signal found in this work, it can be very helpful both for docking and prediction of interactions to understand where this signal comes from. - Dina Schneidman
Barb Bryant
PLoS Session on How to Write a Good Paper
Phil Bourne and Steven Brenner are presenting for the first hour, 10:45-11:40. - Barb Bryant
Having published good papers consistently counts for at least 50% of career advancement. - Barb Bryant
(Phil only published 2 papers in a 10-year period while he was leading the PDB. That was a big mistake for traditional career path, but he wouldn't have done it any different way. It was an issue when he came up for tenure.) - Barb Bryant
Other things that matter in an academic career: Teching/mentoring, gratns, community service, good talks and networking. - Barb Bryant
Steven: For a young scientist, papers matter even more. - Barb Bryant
Steven: When I'm looking at a postdoc or junior faculty applicant, I look at where they trained, who their advisor was. I look at what papers they were first author on. Then, is there any paper that is a real standout and important. Then, how many papers, and what is their nature. - Barb Bryant
Andrej: what your rmentor says about you makes a lot of difference too. - Barb Bryant
Alan Turing - signal processing. At AT&T he gave a talk that was never published; we attempted to reiterate this in a recent PLoS CB paper: 2007 3(10)e213. - Barb Bryant
Phil: Work only on important problems. Work with important people. You have to figure out for yourself what is important. - Barb Bryant
Do this when you're young. - Barb Bryant
You need more than brains: you need courage. The system is not well geared for (especially) young people to take risks. Risky papers are often rejected. We're beginning to see evidence of how the review system fails. The review system supports incremental work better than risky, outstanding work. - Barb Bryant
Take PLoS ONE. PLoS ONE was intended to be a place to put work that may not be enormously innovative, but it is sound. But what has happened is that it got a number of risky papers, some of which have turned out to be important, and highly cited. So this journal that is supposed to be at the lower end of things, has a relative high impact factor. - Barb Bryant
Steven: Examples. Original paper where we wrote about the SCOP database. Very highly cited. Rejected by reviewers; my advisor battled the journal to get it published. My arguably most important paper, identifying targets of nonsense-mediated decay, was rejected by three journals. Most-cited paper in field of alternative splicing or nonsense-mediated decay. Don't be discouraged! If it's important, it will eventually be recognized. - Barb Bryant
Phil: The PDB paper has been cited 10,000 times. Noone has ever read it... - Barb Bryant
Luck favors the prepared mind. - Barb Bryant
Time management is critical. The amount of time in the lab doesn't necessarily translate to productivity. You don't get taught how to manage your time well. Read books on time management. - Barb Bryant
Work from your heart. If your heart is not in it, you won't succeed. You need the passion to go the extra nine yards to do a great piece of work. - Barb Bryant
So all of that was prerequisite to writing a paper. Now, how do you do it? - Barb Bryant
Start writing the paper on Day 1. - Barb Bryant
Draft paper helps focus the work, makes sure that you write it up; is easily shared with colleagues for feedback that can help you with the work itself. - Barb Bryant
Steven: another reason to have it written up early in draft form -- I ignore "in preparation" on a resume. If they say "in preparation, draft available", that makes an impact if I can see the draft. - Barb Bryant
Steven: another reason to write the introduction early: "A month in the laboratory can save you an afternoon in the library." Being forced to write the introduction might help you find previous work that will change what you do. - Barb Bryant
Phil: If you hate writing, get over it. If you do not write well, take classes. Now. - Barb Bryant
? I wonder if they have suggestions for people who just don't have good command of English -- what about working with a writer, etc.? - Barb Bryant
Try to see your paper as the reviewer will see it. Try to look at it "from a distance." - Barb Bryant
It might be motivating to you to realize that the paper is going to be your (scientific) legacy, long after you're gone. - Barb Bryant
Some ingredients of a good paper: novlety, good coverage of the literature, good data, strong statistical support, clarity of presentation, thought-provoking discussion. - Barb Bryant
Look at the scope statements of the journal you're thinking of submitting to. - Barb Bryant
Don't rely on your PI to tell you the novelty of the work - figure it out for yourself. - Barb Bryant
In discussion, guide people to build on the work. - Barb Bryant
DON'T try and prove that you are smart. - Barb Bryant
Avoid the kitchen sink syndrome = putting too much that is not relevant into the paper. - Barb Bryant
Maintain a good bibliographic database (EndNote, RefWorks, etc.). Consult a citation index (ISI, Google Scholar); consider using that to annotate your database entries. Use a tool like Mendeley to store annotations. - Barb Bryant
(Mendeley is a way of annotating PDFs; you can share annotations.) Explore social bookmarking to find out what others have been saying about papers. - Barb Bryant
Q: how important is the citation index of a paper? A: not important. What matters is how good and relevant the paper is. - Barb Bryant
In 2000, Phil wrote a paper on alternative views of looking at protein space. For 5 years, noone cited it. But then it became a hot topic and citations started to pick up. - Barb Bryant
Steven: There is a tendency to have a winner-take-all approach. Everyone will cite one paper, even if there is a more relevant paper. It's important to go out and find out which papers really are most relevant. - Barb Bryant
Steven: Have your whole lab get together and pick one program to store your data. Even if it's not the best program, being able to share the tool is really valuable. Phil: we lack good project management tools that map to the scientific endeavor to allow us to share and maintain output from the lab. Come talk to me about developing a company around this... - Barb Bryant
Phil: Have colleagues critique your paper. - Barb Bryant
Become a reviewer early. Shadow more senior people in reviewing. Look at the other reviews of the paper. - Barb Bryant
Approach program committees of conferences. - Barb Bryant
Hold journal clubs. Identify good and bad papers in journal club and elsewhere and study tehm. A good paper will likely tell a story and be enjoyable to read and follow. It's pitched at the right level for the intended audience. - Barb Bryant
Acknowledge the people who submitted the review. - Barb Bryant
Q: will the program committees and journals accept volunteer reviewers, or do you have to be asked? Steven: There are two ways this can work. First, a PI can invite a student of theirs to help review it. Second, if I can't review it myself, I can recommend someone in my lab to do the reviewer completely themselves. The editor then can choose whether to use this student/postdoc reviewer. - Barb Bryant
Choose the journal wisely. Do you read that journal? Do you cite it? Is it a top-notch editorial board? Does it have highly accessed papers? What is the rejection rate? What is the average time to publication? (Find out by talking to people who have published in that journal.) Is it indexed in PubMed? - Barb Bryant
And, most importantly, does the scope match your work?? - Barb Bryant
Use the presubmission inquiry if the journal has one; it helps in determining scope. - Barb Bryant
Mark: what emphasis to place on how highly cited the journal is? Phil: I don't care anymore at my point in my career. This is my personal opinion. The review process is quite broken. But others judge job candidates by this. What do you think? - Barb Bryant
Mark: shouldn't think about impact factors. - Barb Bryant
Phil: Other communities do not have a review process, but a moderation. Then it is how much it is accessed by the community is the judgment of its worth. - Barb Bryant
Steven: You need to think about who will be evaluating you in your career. Traditionalists will care about which journal. If you are looking for a job right out of post-doc, won't have time to have gotten citations on the paper, so which journal matters more. It helps to have letters of reference that describe the importance of the work. - Barb Bryant
It helps to understand the editorial process. - Barb Bryant
Know that the best scientists get rejected and/or have to make major revisions. - Barb Bryant
Post-review phase. Again, "get over it". Buckle down and do the work. Don't be defensive. Address every aspect of the reviewers' concern. It's fine to disagree with a reviewer, but have the conversation, don't shy away from it. Make it clear how your revision addresses the reviewers' points. - Barb Bryant
Examples of a good paper and bad paper... No time to do this... - Barb Bryant
Steven: Bear in mind that the reason we do science is to create new knowledge and contribute that to the body of scientific knowledge. You do that through your papers. So papers must be an effective conduit. - Barb Bryant
Steven: Ability to communicate is key. Most of us are not great writers. You need to figure out what works for you. Team writing can be very effective. Example: one student had to talk it through first. - Barb Bryant
Share it with colleagues before sending it out for review. - Barb Bryant
Make sure you make it easy for the reviewers. Example: when you make a revision, make it clear what you changed. - Barb Bryant
Figures. When people flip through a paper, they usually look at the figures first. You should invest major effort in getting the figures perfect. You might revise a figure 100 times. I have people in my lab take a course in the visual presentation of information. - Barb Bryant
Steven (still): it's important to make sure that you are right. If you have 10 papers and one has a major flaw, that can be devastating. - Barb Bryant
Surya Saha - just finished PhD and starting post-doc. Has these questions from first-time authors - Barb Bryant
(We are going into the second half of the workshop, with a panel of 7 people) - Barb Bryant
Surya: what happens inside the editorial process of a journal? - Barb Bryant
Nils Gehlenberg - student. Pros and cons for new authors of supporting alternative publishing and evaluation models. - Barb Bryant
Article metrics. At yesterday's future of scientific publishing - I can influence citing in blogs and social networking sites. Should I go out and market my papers? - Barb Bryant
What about publishing that are not papers - like data, or software tools? Will that look good on my resume? - Barb Bryant
Mark Gerstein (experienced author): Scientific publishing in the future. - Barb Bryant
We are seeing a distinction between databases and journals getting blurred. People are approaching reading like databases -- you query for an article. Also, people read database entries, e.g., to find out about gene function. - Barb Bryant
It's hard to fit everything into conventional journal articles or biological databases. Why are people citing SCOP so much (for example)? Are they *reading* it? Or is it associated with a piece of code or database that they're using? The latter, often. - Barb Bryant
People cite a paper not because they read it but because they saw an easy-to-read summary or someone cited it in a lecture that they saw. - Barb Bryant
Mark's view: We can update scientific publishing; make it more multi-tiered, more compatible with the digital world. I advocate a structured digital paper. It's not a single narrative, but a set of streams of information - some computer-readable and structured; one or more stream for the human reader. - Barb Bryant
You do this not as separate from the paper publishing, but as part of publishing the paper. - Barb Bryant
Structured abstract. Structured digital table. (Are examples) - Barb Bryant
Chris Sander speaks next. - Barb Bryant
We have a project: the Factoid Project. - Barb Bryant
Factoid Project: require authors to submit basic facts they've derived to a database. - Barb Bryant
Scientific publishing needs to be revolutionalized. - Barb Bryant
We need to take away power from reviewers and editors. - Barb Bryant
We should engage in marketing our papers (though prefer a different term) - Barb Bryant
We should change how papers are evaluated by potential employers and tenure committees and so on. - Barb Bryant
Talks about figures with (A), (B), (C), and having to find the letter in the caption. Figure captions are hard to read and understand. In Time Magazine, you won’t see those. Appeal: make figures an integrated information panel. Let’s put together a small working group; write up an opinion piece, send it to journals and ask for a change. I’ll help. - Barb Bryant
Chris proposes another working group about assessing a paper’s impact and the author’s contribution. - Barb Bryant
Chris: Doesn't like PLoS Computational Biology because of the goal of increasing the rejection rate to improve impact factor. Optimize scientific contribution not rejection rate. - Barb Bryant
Chris: How your papers get advertised. You can promote your own work. Don't just rely on the editors. Don't just rely on the reviewers. Don't rely on the paper coming out and someone maybe reading it and citing it. Coming here and doing posters. - Barb Bryant
Gary Benson: Professor at BU; editor at NAR. Edits web server issue, an annual special issue. - Barb Bryant
I like papers, says Gary. I like looking at figures. I like when people put a lot of effort into organizing their thoughts. I like it when people use examples in their papers. - Barb Bryant if you're interested to submit a paper. - Barb Bryant
In Comp Bio, people make predictions about something. It's easy to make predictions; it's not easy to validate them. At NAR, we have a strict policy that you have to show considerable evidence of validation, with data that was not used to develop the model you're presenting. - Barb Bryant
Pitfalls for journal submission. - Barb Bryant
Prior publication: Arxiv is an archive; that is not considered (by NAR) a citable publication, so it's OK - would not exclude your article for that reason. On the other hand, we saw a paper previously appearing in PLoS Currents -- and we do consider that a prior publication because cited in PubMed. - Barb Bryant
Conference submissions are prior publications in some cases. Conference proceedings can have fairly large papers, and are usually citable. - Barb Bryant
Open access: this is a journal's way to compete with online repositories. It's a way to make your paper free to everyone. All publishing should be like that - but it costs money. Authors have to pay usually, for open access. - Barb Bryant
The review process at NAR: Senior editor evaluates for meeting scope. Pass it on; next editor again considers scope. If that passes, then get reviewers. Authors are asked to suggest reviewers. If you propose reviewers, pick people who are not your friends but are knowledgeable in the area. - Barb Bryant
We pick 2 reviewers. You appreciate as an editor getting suggestions for reviewers. I usually respond positively to volunteer reviewers. - Barb Bryant
Reviews usually take 2 weeks at our journal. Some are good, some are not. You want more than a paragraph! Then the editors try to make a judgment based on those reviews. If there is disagreement the editors will seek a third review, and this can take additional time. The editor usually informs the author of this delay. - Barb Bryant
We try to have a 30-day turnaround time. Then if the reviews are positive, you get a chance to modify your paper, and our goal is 60 days. - Barb Bryant
Be non-confrontational in your letter responding to the reviewers that accompanies your revised manuscript. This is a dialogue between you and the reviewers, monitored by the editor. - Barb Bryant
End of Gary's introduction - Barb Bryant
Andrej Sali speaks next. - Barb Bryant
Presubmission inquiry - the editor is looking both at scope and at quality. It's important to put effort into this. - Barb Bryant
Suggested reviewer lists: I found through experience that it is difficult for authors to predict which reviewers will be fair or supportive, or negative. You may think someone is your friend, but they are not always your friend. Don't put too much attention onto who you think is your friend. - Barb Bryant
Phil will put his slides on the PLoS CB website; Andrej thinks that’s great, and he’ll be requiring people in his group to go through them. - Barb Bryant
Try to satisfy reviewers. Why not? Obviously, you want to do what you think is right scientifically, so do not compromise that. - Barb Bryant
Collect common wisdom within your lab about writing. In my (Andrej's) group: definitely start with written document on Day 1. Outline the manuscript before you start the project. Keep it up to date as the process goes on. Keep in mind the key idea - why should people read it? Summarize that in the title. No more than 2-3 sentences on the main message. - Barb Bryant
On to Alfonso Valencia, editor of Bioinformatics. - Barb Bryant
What to publish: your work. Where to publish: Bioinformatics, obviously. :-). When to publish: not before my holidays. - Barb Bryant
There is both opportunity and risk. Consider the music industry: the web has had a huge impact; musicians aren't sure how they are going to survive. Newspapers too - huge changes. - Barb Bryant
The web affects not only science reporting but science production. - Barb Bryant
People who have already built a solid scientific reputation can afford to try out and champion new modes of publishing. Young scientists have to be much more careful so as not to harm their career. - Barb Bryant
Not all papers are equal. Application notes are different than scientific papers are different than discovery notes. - Barb Bryant
It's more important to be able to build on a paper than to reproduce the paper. A good paper enables more research. - Barb Bryant
Publications are an essential instrument not only for knowledge distribution but also as a tool for organizational decision-making: evaluation of institutions, grants, fellowships, positions. - Barb Bryant
Before replacing impact factors, think: with what? - Barb Bryant
You don't have to do all that the referees/editors ask for, even if it means your paper gets rejected. Use your own scientific judgment. - Barb Bryant
Build on others' work. Quote them fairly and with respect. - Barb Bryant
Discuss your results in meetings and with colleagues before publishing. In bioinformatics, the risk of being scooped is minimal. The benefit of sharing and getting feedback is enormous. - Barb Bryant
bb, thanks for the comprehensive coverage! - Ruchira S. Datta
You're welcome! :-) - Barb Bryant from email
Thanks! - Mr. Gunn
A big thank you for the coverage bb - Yann Abraham
yes, just great, bb! - Claudia Koltzenburg
Keynote: George Church - BI/O: Reading and Writing Genomes
George Church has developed an amazing amount of technology. - Barb Bryant
I am always wondering that if he gets any sleep at all. - Dawei lin
Which is the introducer? - Dawei lin
michal linial, if I'm not wrong (which I was, need new glasses) - arne
The My First DNA sequencer reference: - Shannon McWeeney
First challenge on computational interpretation and integration: personal genomes =stem cell epigenome + mC environments + traits. - Dawei lin
Olga Troyanskaya - Barb Bryant
Cost of drugs goes up linearly; cost of sequencing is dropping exponentially - Barb Bryant
40,000 fold price drop for 4 years - Dawei lin
CGI price for genome is $1500/year? - Dawei lin
In 2005 we abandoned a monopolistic capillary electrophoresis; instead we have a couple and now 21 different technologies for sequencing. Resulted in a jump in rate of change of sequencing capacity - Barb Bryant
He thinks that many of the sequencing companies will find a niche :) - arne
Cost of personal genome: 2007: $57M; 2009 $1500, for 40-fold coverage. - Barb Bryant
Close to the $1000 genome - arne
(+ $100,000 interpretation cost?) (he doesn't really think that) - Barb Bryant
Drmanac et al Science Jan 2010 - Dawei lin
Sidetrack: One friend said when he started his PhD it took 6 month to sequence a bacteria and 6-60 month to analyse it. Not it takes 6 minuted to sequence it and still 6-60 month to analyze it. - arne
limitation is several hundreds nm in scale on chip (positive charge molecules on hydrophobic background - Dawei lin
7% human genome is missing so far because of technical challenges - Dawei lin
trio genomics information (father, mother, child) is increasing important in genomics research - Dawei lin
From open acess Sequences to Bio-Fab - arne
One of the 21 sequencing technologies is open-access. Reads and writes DNA with light. - Barb Bryant
2nd-gen synthesis ($500 per 15 Mbp) - arne
Second-generation synthesis - four different kinds of technologies. - Barb Bryant
Next Gen synthesis: off chips $500 15Mbp - Dawei lin
Tian et al 2004 Nature - arne
The work started around 2003 - Dawei lin - arne
person genome 3M allele -> immunology + microbome -> trait - Dawei lin
Issues of personal identification from genomic data. Informed consent as one solution. - Barb Bryant
Have 16,000 volunteers for Personal Genome Project so far; 100,000 target. - Barb Bryant
Claims that ~1800 genes are highly predictive and medically actionable. - Barb Bryant
They are rare but collective common at 10% level - Dawei lin
Example of the Madsen family with two diseases. Found causative allelles - 4 total (2 from each parent). - Barb Bryant - Dawei lin
Each time we find a scary allele in a person, it could be a sequencing error; it could be a problem with the literature. - Barb Bryant
found a dozen cases in the literature got allele sequence wrong - Dawei lin
The oldest volunteer for PGP is 96.7 years old - Dawei lin
Q: Are these genomes available ? - arne
Circulating tumor, pathogen, fetal, and immune cells. - Barb Bryant
Microbe vs Immunome - arne
If you want to look for a microorganism in a body, you can either look directly for the microbe, or look for the body's reaction. - Barb Bryant
immune test is to focus on response to exposure. - Dawei lin
Sequencing after vaccination - response is maximum after 7 days - arne
Generating human tissue from pluripotent stem cells - Barb Bryant
The Economist 20-May-2010 cover - Dawei lin
Genome engineering - Barb Bryant
E.g., change the genetic code -- for resistance to pathogens, new amino acids, and something else. - Barb Bryant
You have to do this safely. - Barb Bryant
For $400M, Dupont made 27 changes to the 4.6 Mbp E. coli, to make a chemical. - Barb Bryant
Another application: bio-petroleum from microbes. - Barb Bryant
Identify enzymes that synthesize alkane. Many cyanobacteria made trace amounts; others made none. Did genome sequence "subtraction" to find which genes were in the former. Isolated & tested these genes. Overproduced them; it worked. Green chemistry. - Barb Bryant
Multiplex Automated Genome Engineering (MAGE)... - Barb Bryant
Church's own genome is available: - Christiaan Klijn
So: subtract my genome from Church's, then overproduce those genes --> TOTAL BRILLIANCE! - Barb Bryant
Example of freeing up a codon by changing those codons to a different one./ - Barb Bryant
Is this not just the analysis. Not the sequence ? (or did I miss a link) - arne
See the 'Datasets' header -> you can get 500k Affy data as well as exome - Christiaan Klijn
Metabolic engineering example. Historically, you'd get obsessed with one step in the pathway and overproduce one enzyme. But then you'd get product inhibition, or the product might be toxic. - Barb Bryant
Would be nice with a map to the reference genome as well, but guess that can be done - arne
DNA Nanostructures: (DNA origami). Proposes a combination of DNA and proteins. - arne
DNA nanostructures help solve structures of membrane proteins. - Barb Bryant
First practical application: Made a long rod that was stiffer than other DNA. Used in NMR for membrane proteins (Cooooll idea but, it has been tried with proteins before) - arne
caDNAno is a software tool that is free available - Dawei lin
Time for questions. - arne
Roland Krause
Is there interest in a Birds of Feather session tomorrow regarding (micro) blogging?
... or simpy a joint luncheon? - Roland Krause
joint luncheon sounds good. - Mickey Kosloff
mentioned this before but might have been lost: if ISCB has to do something to support this crucial activity: let us know! - Burkhard Rost
OK, then let's meet for lunch tomorrow. Please spread the word. It'll be easiest if we meet at 12:50 at the hallway leading to the ballrooms on the 3rd floor. Burkhard: Thanks for the support, we'll get back to you. - Roland Krause
@Burkhard: most people that sat next to me had no idea about this room or about FF, despite the prominent slide and the links from the ISMB webpage. Perhaps if you show a screenshot before a keynote, awareness will increase? - Mickey Kosloff
Afraid the horrible wireless connection made (live) blogging nearly impossible for many sessions. Was going to cover the late breaking research session today from 201, but no luck. - Oliver Hofmann
Must have missed you. Got there a couple of minutes late and didn't see anyone. - Mickey Kosloff from iPod
Hmm, let's try to meet at the reception. It'll be a search in 2D space so we should find each other in finite time. I will be in room 302 for the remainder of the afternoon. - Roland Krause
What about another projector projecting the feed, in talks by some daring presenters? - Barb Bryant
I won't be able to make the reception. My 3 ideas are: separate (secure) wireless for bloggers. Incentives (e.g. Priority for plos-cb postcard publications). Wider campaign to recruit micro bloggers before ismb. - Mickey Kosloff from iPod
1. projection of the feed: don't get the reason. 2. wireless 4 blog: good idea, 3. plos-cb postcard slot: will talk to phil/plos, 4. other incentives: what you want? - Burkhard Rost
Reason for wireless4blog is most likely due to low speed here - arne
It's not a bandwidth problem, I had throughputs on the MB/s. More likely, many of our computers have problems in this mixed settings with "smart" handling of receiver power etc. In Vienna, I had a clever tech guy that helped to disentangle these issues with my network card. What we (all) would really need is some sort of true hacker with proper equipment but I have no good idea how to recruit such a person. - Roland Krause
Can bottleneck be between local server and ISP ? - Mickey Kosloff from iPod
Special Public Lecture: Dr. Robert Weinberg - Cancer Stem Cells and the Evolution of Malignancy
Shows picture of stages of cancer progression (ref Vogelstein, colon); poses the question of how metastasis occurs -- does this involve genetic or epigenetic changes? - Barb Bryant
Tan Ince cultured two kinds of normal human mammary epithelial cells. He transformed them with oncogenes, resulting in different types of tumors. - Barb Bryant
Concludes that the nature of the normal cell of origin is a strong determinant of the phenotype of the primary tumor, and whether it metastasizes. The playing field is tilted in the beginning. - Barb Bryant
Posits tumor-generating cells. - Barb Bryant
Self-renewing stem cells produce either more stem cells or transit amplifying cells which in turn lead to post-mitotic differentiated cells. Only the self-renewing stem cell could seed a new tumor. - Barb Bryant
invasion-metastasis cascade - Barb Bryant
How do cancer cells acquire all of these capabilities (invasion, intravasastion, transport, metastasis...) Are there addiitonal mutations required? Is it epigenetic? - Barb Bryant
epithelial-mesenchymal transition -- cells on the perimeter of the tumor are mesenchymal. This may be due to signals from the surrounding stroma. - Barb Bryant
There are probably 1000 proteins that shift in EMT. Vaious transcription factors (TFs) induce EMTs. - Barb Bryant
EMT program highly complex and occurs normally during development. - Mickey Kosloff from iPod
It seems likely that most of the invasion-metastasis program can happen without need for additional mutations; rather use signaling from microenvironment. - Barb Bryant
P. Gupta transformed human primary melanocytes (pigmentation in the skin) with a cocktail of oncogenes. Found that in contrast to transformed epithelial cells, there was much higher likelihood of metastasis. Again, cell of origin is important in future behavior. - Barb Bryant
One TF, Slug, was found to enable melanoma metastasis. (Even though the primary tumors grew a little faster.) - Barb Bryant
Another TF, FOXC2, when expressed in epithelial cells induces migration and invasion. A subset of breast cancers have high levels of nuclear FOXC2, and these are more aggressive breast cancers. - Barb Bryant
Speculates that different networks of EMT-inducing factors might program metastasis in different cell types./ - Barb Bryant
Stem cells identified by high CD44 and low CD24. (CD's are markers on cell surface which can be assayed fairly easily.) - Barb Bryant
There are various ways to make cells acquire stem cell characteristics. - Barb Bryant
Mentions Kornelia Polyak. There are stem-like cells in primary human breast samples. The stem cell program in normal human mammary gland is coopted by cancer cells. - Barb Bryant
More proof that EMT creates stem cells. - Barb Bryant
Most current chemotherapies preferentially kill non-cancer-stem-cells. The remaining stem cells can repopulate the tumor and are often more resistant to therapies. - Barb Bryant
Gupta & Onder tested CSCs and non_CSCs with a bunch of drugs. There are some CSC-targeted agents (Salinomycin, Abamectin). Of 16,000 compounds only about a dozen preferentially killed CSCs as opposed to non_CSCs. Many were the other way round. - Barb Bryant
This probably won't be the "answer". Christine Chaffer noticed that there were some floating cells in 2D cultured human mammary epithelial cells. She grew these up; these look more like CSCs. - Barb Bryant
Interestingly, she found that non-CSCs could generate CSCs. - Barb Bryant
Hm, isn't this kind of pouring cold water on the excitement about CSCs as drug targets? Or maybe you have to target both CSCs and non-CSCs simultaneously. - Barb Bryant
yup - Barb Bryant
Q: cancer biologists like to study druggable genome. But transcription factors seem most important. A: expression of TFs is controlled by cytoplasmic factors. Might want to go after those. Drugging the TF itself might be hard, but the signaling pathways might be more druggable. - Barb Bryant
Q: has it been shown that change in the two forms of cadherins match the change in CD expression, and are these correlated with morphology? A: I showed that: CD44 high cells shut down E-cadherin; they expression vimentin, and other mesenchymal markers. I don't know whether CD44 is useful for non-mammary epithelial tissues. - Barb Bryant
Q: So do normal non-SCs generate SCs? A: Yes. Same differences as in cancer. - Barb Bryant
Spontaneous de-differentiation into SCs. Interesting phenomenon. - Steve Chervitz Trutane
HL40: Martin Vingron - Histone modification levels are predictive for gene expression
See PNAS 2010 Feb 16. - Barb Bryant
Using histone modification data in Barski et al and Wang et al and one other. - Barb Bryant
Li, Carey, Workman 2007 Cell 128:707 review. Tabulates distribution of modifications along the genes. - Barb Bryant
Some are activating; some repressing; some either. Occur in various locations along the gene. - Barb Bryant
They want ot go from histone modification vector to transcription level. - Barb Bryant
Zhao lab data: 38 histone modifications. Look in promoter region. - Barb Bryant
-2000 to +2000 around TSS. Introduce a pseudocount alpha: x = log(N + alpha). - Barb Bryant
Standard linear regression. - Barb Bryant
Graph of predicted vs measured log expression values. High correlation. In fact, it looks bimodal. - Barb Bryant
Looked at where the information resides. Tried using single, pair or 3 modifications and see how close can get to optimal prediction. - Barb Bryant
Most predictive modifications are H4K20me1, H3K27ac, H3K79me1, H2BK5ac - Barb Bryant
Shows a histogram of promoters with respect to CpG ratio. - Barb Bryant
Which modifications are informative depends on CpG content. CpG rich: H4K20me1, and to some extent H3K27ac, H2BK5ac some. CpG-depented: H3K4me3, H3K79me1. - Barb Bryant
Predicting in other cell types. Cui et al 2009: ChIP-seq data for CD36+ and CD133+ T cells. 10 histone mods (H3K4me1/3, H3K27me1/3, H3K36me3, H4K20me1, H3K9me1/3, H2A.Z) + gene expression data. - Barb Bryant
Trained a model for those 10 mods on initial dataset, then tested on the new data. Prediction still pretty accurate. However, these cell types are quite closely related. So looked at genes that are differentially expressed between the cells. Even there, th eprediction is still pretty good. - Barb Bryant
H4K20me1 and H3K79me1 associated wtih elongation; H3K4me3, H3K27ac, H2BK5ac are sasociated wtih the TSS. - Barb Bryant
Summarizes: expression and histone meodification levels are quantifiably related. This holds across cell lines - Barb Bryant
Common prejudice: Low-CpG promoters drive tissue specific genes. - Barb Bryant
PT43: Emmanuel Douzery - SUPERTRIPLETS: A triplet-based supertree approach to phylogenomics
Supertree methods can be used to build trees from diverse trees on incongruent species sets and diverse data, e.g. morphological and phylogenetic data. - Roland Krause
How to find the best representation of several trees. Distances between trees with different taxa. - Roland Krause
HL38: Kyoungjae Won - Applying histone modification information to genome-wide prediction of transcription factor binding sites
Started with 8 histone modifications as training data, and 13 transcription factors (ChIP-seq binding data; evaluation set) and another evaluation set. All in mouse stem cells. - Barb Bryant
Shows example Oct4, with enhancer specific binding properties - low H3K4me3 and high H3K4me1. - Barb Bryant
To train a model for Klf4: looked for high H3K4me3 with the Klf4 PSSM; at teh enhancer looked for high H3K4me1/2 and Klf4 PSSM. - Barb Bryant
His software/method is called Chromia. - Barb Bryant
Train with HMM; 3 HMMs, one for promoter binding Klf4, one for enhancer binding Klf4, and one for background. - Barb Bryant
Conservation information seems to worsen the predictions! - Barb Bryant
Used RNAi against the TF - Barb Bryant
Used a 3-state HMM, which captures the spatial pattern of histone marks - Barb Bryant
Chromia predicts locations of enhancers and promoters. Chromia predicts nucleosome free regions. - Barb Bryant
Publication: BMC Bioinformatics - Barb Bryant
Colleagues Wei Wang, Bing Ren, Robert Shoemaker, Iouri Chevelev - Barb Bryant
Reference for this work: - Barb Bryant
Question about relative weight of PSSMs and histone marks in the models. - Barb Bryant
PT34: Chun-Nan Hsu - A Spectral Graph Theoretic Approach to Quantification and Calibration of Collective Morphological Differences in Cell Images
PT41: Steven Kelk - Phylogenetic Networks Do not Need to Be Complex: Using Fewer Reticulations to Represent Conflicting Clusters
Many reasons to obtain conflicting trees, some have legitimate reasons (hybridization etc) which can be modeled as phylogenetic networks. - Roland Krause
Clusters are subset of leaves, basically a hypothesis that at least one trees contain such a clade. - Roland Krause
Clusters loose the topological information. Let's the user specify data that are trusted. - Roland Krause
Minimize the number of reticulations, motivated by parsimony but by evolution. - Roland Krause
Algorithm CASS attempts to produce such networks and does so well (60 slide of math not shown) - Roland Krause
Tested on different subsets obtained from a Poaceae grass data set (PWG 2001, Smidt 2003). Comparison to Hybrindinterleave, PIRN, Galled Trees and Cluster Network. - Roland Krause
CASS works well in practice. Integrated in Dendroscope. Running times slightly longer than competitors. - Roland Krause
HL35: Liran Carmel - A universal relationship between gene compactness and expression level in multicellular eukaryotes
From Eugene Koonin's group: - Roland Krause
Different lengths for a gene - total transcript length, 5'UTR length, introns, etc - Roland Krause
Expression levels are collapsed to a single value by ranking by condition/tissue into 3 category and average and round the resulting rank. - Roland Krause
First observed in C. elegans - Roland Krause
Found in other organisms and for several length measures and different strategies for expression. - Roland Krause
20 nucleotides are transcribed in one second - Xinwei Han
one nucleotide needs two ATPs - Xinwei Han
Intergenic length and compactness are related. - Roland Krause
Plants have opposite trend - Xinwei Han
Exception in plants: highly expressed genes are least compact. - Roland Krause
No good explanation for the outlier, usually selection and genomic design are given. - Roland Krause
New explanation: the relationship is not monotonous but peaked. - Roland Krause
Segmented regression recovers the relationship easily. - Roland Krause
Use of mixed gamma distributions to estimate noise and real expression level by tissue. - Roland Krause
Selection rather than genomic design shapes the length distributions. - Roland Krause
Q: Relation of intron length and alternative splicing. A: Probably not. - Roland Krause
Q&A: Intron length changes more pronounced than exon lengths. - Roland Krause
Q: Specific tissues: A. Interesting but not yet analyzed. - Roland Krause
HL36: Zhidong Tu - Pathway and network based approaches to prioritize reliable hits from high throughput RNAi screening experiments
He points out that there is work just published that is quite similar to their work - - Shannon McWeeney
integrative approach - see work in Drosophila BMC Genomics 2009 10:2220; siRNA and PPI - Genome Research 2009-19:1057-1067 - Shannon McWeeney
key assumption - real hits will not be randomly distributed in physical interaction network - should reside in subnetworks - Shannon McWeeney
Ranking algorithm to compare query node with rest of nodes with known hit/non-hit status (NePhe score is then summarized) - Shannon McWeeney
trade-off between quality of hits and algorithm choice - Shannon McWeeney
Assumption that hit is not randomly distributed assumes that RNAi is hitting its Target. Results from random naming seems to validate that this assumption is reasonable. - Michael Jones from Android
HL33: Todd Gibson - Neofunctionalization in interaction network evolution
Fate of duplicated genes: non- neo- and subfunctionalization. - Roland Krause
In networks of interacting proteins duplication leads to duplication of interaction. - Roland Krause
function = interaction - Roland Krause
link dynamics: new interaction maps to neofunctionalization, loss of interaction to subfunctionalization - Roland Krause
He and Zhang 2005 calculated neofunc. The older the duplication, the more interactors. - Roland Krause
Wagner 2001/2003: Ancestral protein would self-interact and form expected interaction. If no self-interaction, de novo interaction can to be assumed - Roland Krause
Binding domain in yeast-two hybrid is a dimer. Self-interacting proteins should not be observed. - Roland Krause
Modeling neofunctionalization in a theoretical network. - Roland Krause
Highlights the importance of self-interactions in network evolution. - Roland Krause
HL32: Ernest Fraenkel - Network models for understanding what 'omic data really mean.
Omic data don't mean what you think - Roland Krause
The answer is 42 - arne from iPhone
Generally little overlap between different experimental screens. - Roland Krause
Studies 156 perturbations mapped on networks - arne from iPhone
Chip chip data and protein protein interaction data. Transcripts and proteins are separate entities. - arne from iPhone
Hitting central nodes. - arne from iPhone
TT32: Scott Cain - GMOD Presents GBrowse 2.0 and JBrowse
LBR17: Dina Schneidman - Integrative Structure Determination of Protein-Protein Complexes Using SAXS, EM and NMR
p110-p85 complex - arne
Similar to Lego assembly - arne
combine different types of data/constraints to solve the docking problem - Mickey Kosloff
used patchdock for rigid docking - Mickey Kosloff
SAXS: Using a FFT can provide distance between atoms (on average) - arne
3D-EM: Density map. Superposition to model. fit score - arne
2D-EM: Similarity - arne
Fast mapping by NMR spectroscopy - arne
FIREDOCK (a method for fast flexible refinement) - arne
Example: Antigen - antibody target.. - arne
Hmm.... my posts never appeared !! - arne
had strange delay problems during keynote - Mickey Kosloff
HL30: Rohith Srivas - Genome-Wide Association Data Reveal a Global Map of Genetic Interactions among Protein Complexes
use of co-localization filter to assist in interpretation - Shannon McWeeney from BuddyFeed
TT30: Matt DeJongh - The Model SEED pipeline for Genome Scale Metabolic Modeling
Excellent demo and very useful web-based application for genome metabolic modeling. - vivek
Keynote: David Altshuler - Genomic Variation and the Inherited Basis of Common Disease
Altshuler is an expert on diabetes type II. - Dawei lin
It is said that he is also a good dancer. - Dawei lin
Tap, ballroom, or tango? - Ted Laderas
Slide dancing - Dawei lin
motivation is to understand genetic basis of human diseases - Dawei lin
Genetic basis of human diseases - important disease mechanisms and bio pathways remain unidentified - Venkata P. Satagopam
gap in knowledge of human disease biology contribute to high failure rates in drug development - Dawei lin
Why understanding genetic mechanisms ? (1) Important mechanism remain unidentified (ii) Gaps in knowledge causes failure rate in drug development - arne
It will be a long way to know if the two motivating hypotheses are true - Dawei lin
one of the most research on T2D. It scaned 100k people for 10 yrs - Dawei lin
10 years later 50% progressed to have the disease - Dawei lin
10years of diabetic research - the out come is - 50% of people with good lifestyle improved - Venkata P. Satagopam
lifestyle has a bigger impact than Metformin - Dawei lin
Diabetes study with 10-year follow-up of diabetes incidence and weight loss, "T2D". Randomized into treatments: lifestyle, metformin, placebo. Best drug makes relatively little difference in incidence; lifestyle intervention is better than drug but still doesn't help a whole lot. - Barb Bryant
best prevention was extensive lifestyle changes (50% -> 40% incidence) - Mickey Kosloff
Diabetes is not only a matter of life style - arne
success rate in current pharma industry is <5% of molecules entering the clinical trails - Venkata P. Satagopam
This is bad !! - arne
mentions well known number of >95% failure rate of new compounds - Mickey Kosloff
because there are still 40% people got the disease after the lifestyle change, it seems that people do not know the course of the disease - Dawei lin
Genetic mapping started in 1913 - Dawei lin
genetic map came in 1913 - Venkata P. Satagopam
Morgan and Sturtevant 1913 - arne
emphasizes he advocates a genetecist's approach (rather than a genomic approach) - Mickey Kosloff
And tells you to skip undergraduate work if you have something better to do - arne
key attributes of genetic mapping - unbiased by prior assumptions about pathways - Venkata P. Satagopam
saturation mutagenesis reveals pathways - Venkata P. Satagopam
key attributes of genetic mapping: (1) unbiased by prior assumptions about pathways (2) saturation mutagenesis reveal pathways - Dawei lin
many mutants -> reveals coherence of pathways - Ted Laderas
These days we have other methods that are unbiased like expression profiling, but genetic mapping has some unique characteristics relative to these (he’ll explain in a minute). - Barb Bryant
Drosophola's mutations looked initially random, years they almost all related to pathways. - Dawei lin
bottleneck is functional determination - biochemical approaches - Ted Laderas
A lot of current knowledge can track back to genetic mapping - Dawei lin
Botstein and Fink Science 1988 .... - Venkata P. Satagopam
A slide based on Galzier et al, Science 2002 - Dawei lin
genetic mapping of human single gene disorders ...over 15 years Botstein paper in 1980, first genetic map in 1985 .... - Venkata P. Satagopam
It took 10 year to find maker for Huntington disease - Dawei lin
Once you find a linked region from genetic mapping, it still takes a long time to find the specific gene responsible. - Barb Bryant
in the 1990's the idea was that common diseases were caused by rare mutations with large effects - arne
"Chromosome shlepping" - Eic Lander's term for the identification of a very gene in some genomic region. - Roland Krause
It is robust to find mendelian disease but to not common diseases - Dawei lin
another approach: population genetics - QTL approach - Ted Laderas
phenotypic variation is often continuous and may involve variation in many genes - Dawei lin
Galton invented regression analysis to analyze the measuring of phenotypic data (heights of parents and offspring). - Roland Krause
The biometric unit --- almost nothing was Mendelian - arne
Most traits are continuously variable - Ted Laderas
Francis Galton was a cousin of Darwin. Darwin didn’t explain the source of variation. Galton focused on this; he measured the heights of parents and their offspring, and found a relationship. He invented regression analysis to draw the line. The slope of the line is related to the inheritability of the disease. - Barb Bryant
It was studied by the cousin of Darwin, Francis Galton (1885) - Dawei lin
phenotypic variation is often continuous ... some history ... Francis Galton (1885), Ronald Fisher (1918), Hermann Muller (1920) - Venkata P. Satagopam
This gave rise to the biometric movement – measure every living thing. Traits were related to genetic relatedness; and it wasn’t Mendelian. This led to the biometric-Mendelian debate. - Barb Bryant
Ronald Fisher, was actually a geneticist, who also invented p-value and Fisher exact test - Dawei lin
Ronald Fisher (the one with the exact test) was also a geneticist. - Roland Krause
Solved by assuming that phenotype often is an effect of several Mendelian genes. - arne
Fisher: individual genes are mendelian, effects of genes additive - Ted Laderas
Hermann Muller 1920 (Nobel Prize for X-ray induced mutations). PhD thesis not Mendelian trait, but truncate wing. Wasn’t Mendelian. Did genetic mapping. - Barb Bryant
Hermann Muller decided to use broken wing of fruit fly to study non-Mendelian diseases - Dawei lin
Muller 1920 paper: 4 chromosomes in fly – 3 contain genes that influence the trait truncate wing. Muller wrote about implications for human traits, like psychological traits. Said that traits were going to be too complicated. Said you could figure out by looking at population, but not looking at Mendelian inheritance in families. - Barb Bryant
Muller 1920 suggested that it needed to do study on a population. - Dawei lin
Muller: Truncate wing - 3 genes influence effect of phenotype - Ted Laderas
Mullers thesis included the notion of surveying complex phenotypes in the population rather than families. - Roland Krause
Muller: traits are too complex to observe in families, but can observe in population - Ted Laderas
characterization and catalogue human seq variation is a decade of work .. i.e international HapMap project - Venkata P. Satagopam
Another decade-long failure: the candidate gene approach. Instead, we need a genome-wide, unbiased approach. - Barb Bryant
Testing candidate genes was not successful. Only 10-20 successes. - Dawei lin
779 GWA published for 148 traits - Mickey Kosloff
out come - 779 published GWA for 148 trails - Venkata P. Satagopam
For common diseases, GWA was needed - Ted Laderas
but "correlation does not imply causality" - Mickey Kosloff
There have been 779 genome-wide association studies (or regions/genes found?) for 148 traits, with p < 5x10^-8 - Barb Bryant
"correlation does not imply causality" .... - Venkata P. Satagopam
But correlation does not imply causality. - Barb Bryant
The reasons of "Correlation does not imply causality": irreproducibility, lack of randomization, confounding, arrow of time. - Dawei lin
If you can't randomize the experiment you can never prove causality as opposed to just being correlated to the underlying cause. - Barb Bryant
FF lag results in all these duplicate posts - Mickey Kosloff
a lot of efforts are on finding correlation between rare variation and diseases - Dawei lin
rare variation is defined as has <5% in population - Dawei lin
95% of variations is already present in the database - arne
Identified 50 regions that are associated with T2D - arne
with in next few years ... the role of rare and less common variants will be characterized in a variety of diseases - Venkata P. Satagopam
next topic - can we obtains new insights into the basis of disease? - Venkata P. Satagopam
one example - sickle cell anemia - Venkata P. Satagopam
Sankaran et al Science 2008 - Venkata P. Satagopam
Lettre et al PNAS 2008 - Venkata P. Satagopam
Uda et al PNAS 2008 - Venkata P. Satagopam
Crohn's disease: 15 years, no idea what was happening. Now many genes and 3 pathways are identified to be relevant. - Dawei lin
96 loci explain ~25% of cholesterol levels - Mickey Kosloff
Lipid GWAS found 60 loci that are previous unknown. Some of the positives are drug targets already. - Dawei lin
Global lipids consortium, forthcoming Nature paper (Nature paper is mentioned about 20 times !!!) - arne
is there a way to automate validation/function determination? - Ted Laderas
prediction -- will prediction prove useful --this is depending on the clinical testing and the genetic test - Venkata P. Satagopam
prediction will be useful when there's a proven intervention - Mickey Kosloff
BRCA1/2 risk for cancer as an example - Mickey Kosloff
seq tech will increase the reach of genetic methods - Venkata P. Satagopam
mendelian fallacy - sub-populations are easily divisible in terms of risk - Ted Laderas
Prediction will only be useful if there is an intervention that you would not use without the prediction. Otherwise, you should use the intervention anyway. - Roland Krause
Huntington will not be a representative example - for most diseases/people identified risk will be <<100% even with full genetic information - Mickey Kosloff
Cautionary tale - PSA prediction results in over-treatment, hasn't been shown that people live longer because of test - Mickey Kosloff
Very cautious about PSA - no improvements on the mortality but many operations performed. - Roland Krause
genetics offers a path to discover the underlying biology of human diseases ; the great value will drive from pathophysiology and treatment - Venkata P. Satagopam
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