Systems Biology DREAM(s) Big

Remember CASP? Critical Assessment of Techniques for Protein Structure Prediction - the biennial competition to computationally predict the precise 3-D shape of an array of target proteins from their amino acid sequences. CASP is now 12 years old, quite an accomplishment really, and a meeting to evaluate the results of the CASP7 predictions is scheduled for this month (Nov. 26-30) at Asilomar Conference Center, Pacific Grove, Calif.

In CASP1 (1994) there were 33 prediction targets, and 35 predictions groups participated. In CASP7, 104 targets have been released, and 200 "human" groups of predictors and 98 "prediction servers" have registered. I don't fully know what the latter group constitutes but will look into it. You may recall that HHMI investigator David Baker's predictions were consistently near or at the top. He seems to have the gene for protein structure prediction.

Now comes DREAM - Dialogue on Reverse Engineering Assessment Methods - which hopes to conduct a systems biology contest and education program that's modeled loosely on CASP. The D can interchangeably be used for Database, says DREAM co-organizer Gustavo Stolovitzky, manager functional genomics and systems biology, the computational biology center at IBM T.J. Watson Labs.

Working with NIH funding and support from the New York Academy of Sciences, DIMAC (Center for Discrete Mathematics and Theoretical Computer Science), and IBM, the DREAM project plans to collect data and techniques researchers can use to understand how well their various reverse-engineering methods actually work. Andrea Califano of Columbia University and Stolovitzky are co-organizers, and the group held its first planning meeting last spring and its first workshop in September.

DREAM is an excellent idea. At Bio-IT World's annual conference last year, directly following a session on systems biology, one attendee and I talked about how terrific it would be to have a CASP-like shoot-out for pathway prediction tools. Little did we know that DREAM's first organizational meeting had already taken place (March). And DREAM is much more than a shoot-out. Speaking at last month's Regulomics Symposium, organized by Cambridge Healthtech Institute, Stolovitzky provided an update.

"We have seen today several very interesting attempts to reverse-engineer or infer biochemical pathways from data," Stolovitzky told the audience. "So the reason the DREAM project came to life is because we don't know whether these methods are giving us the right results or if sometimes we "cherry pick" the methods results that best allow us to publish a paper."

One problem is the lack of a gold standard to measure results against. CASP, of course, uses the structure as determined by x-ray crystallography. "We are trying to determine what would be a gold standard now and what kind of metrics to use to determine if one reverse-engineering method is better than another," says Stolovitzky. "We're also trying to decide whether a database would [help] unify this field."

Not everyone is excited about the idea, concedes Stolovitzky. Someone's favorite algorithm might get dinged; papers based on the algorithm might be called into doubt; grants might become imperiled. As Stolovitzky points out, "a lot of us have been publishing these networks [and] they enrich the literature and [sometimes] they pollute it." A survey conducted among attendees to the first workshop was positive but, interestingly, the proportion of thumbs up from informaticists rather outnumbered those from traditional researchers (disciplines were self-selected).

Working out kinks will take time, but this is a DREAM worth pursuing. Extracting real biological understanding from the staggering amount of omic data is the next big challenge. Static signatures, though useful, aren't enough. We need to know what the biology is.

Pointing to a particularly nasty network diagram, Stolovitzky recalled comments made by a colleague about one of his students who coined the term - Rediculome. The student noted, "We put together all these rediculograms and you will have a Rediculome." Great line, whether original or not. Stolovitzky says the first DREAM competition is probably a year away. More information can be found at the New York Academy of Sciences.

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Pathway Pioneers See Fewer Arrows

Last year, Upinder Bhalla from the Tata Institute in Bangalore argued that modern pathway analysis tools could have detected Vioxx's off-target effects when it was first in trials in 1999. Last summer, Ken Paigen, Director of the Jackson Laboratory explained to Ingenuity Systems' inaugural user group meeting his use of pathway tools to map the functional organization of the mouse genome. Next spring, William Ricketts of Oncotech will present at a CHI's Molecular Medicine Tri-Conference work using pathway analysis to identify signaling factors implicated in cisplatin resistance in ovarian cancer.

Innovative uses for pathway tools and exciting results from early users are sprouting like mushrooms after a spring rain -- albeit following a few harsh winters. Three years ago pathway pioneer Ingenuity Systems had fewer than 1,000 users. Today, CEO Jake Leschly says there are 10,000 Ingenuity users. Fellow pioneer and rival, GeneGo claims its market penetration is even bigger -- and, of course, that its tools are better.

Whatever the precise numbers, it is clear that the adoption of pathway analysis tools is growing and giving the beleaguered informatics sector something to cheer about. Take, for example, the comments of Venkateshwar Keshamouni, assistant professor in the Department of Internal Medicine at the University of Michigan:

"One senior professor said to me, 'These software tools don't do anything that a dedicated graduate student cannot do on his own by doing PubMed searches.' He's probably right, however it is pretty darn good if a software can consistently substitute for a dedicated graduate student. Literally with the click of a button these tools can provide a good overview of what is already known about the data set of interest, including potential interactions."

Don't get the wrong idea -- it's not all quick leads and validated biomarkers -- but pathway analysis tools are gaining traction with researchers. They represent a multi-purpose arrow in the research quiver that straddles knowledge management and knowledge creation. Bio-IT World this month has published a fairly substantial feature examining pathway analysis technology and adoptions trends.

Click to read the full article

Related Links

Computational Cell Bio Meeting 

Supercomputing Center Gets $8.5m Award for Biomedical Modeling 

Protein Structure Initiative Launches New Resource

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