Sadly the original link maestro posted seems to have gone dead.
Here is another open source bioinformatics attempt. Sage Bionetworks.
When he and other scientists in his field began their work, biologists had long thought that common diseases like cancer and heart disease could be characterized by identifying a single cause — perhaps an errant gene — and treated with a drug aimed at that gene, or, more likely, the protein the gene produced.
Some of the drugs developed that way were great successes, like Herceptin for breast cancer and antiretroviral drugs to treat AIDS. But these are the exceptions. According to a 2004 study in Nature Reviews, 89 percent of drugs that enter human clinical trials fail, usually because of unanticipated side effects.
The problem is no surprise to Dr. Schadt. “It turns out that common diseases involve thousands of genes and proteins interacting on complex pathways,” he said.
In 2003, Dr. Schadt was first noticed as a co-author of a paper in Nature that articulated the need to move beyond the impact of individual genes on disease and to create computer models of diseases that included the interaction of genes and proteins.
Here in lies the debate between the SENS approach and the evolutionary/genetic approach to not only curing disease but ultimately reversing aging. Metabolism and the genetic pathways that create diseases (cause damage) are extraordinarily complex. The end damage is a more easily understood target. Dr. Rose says that genomic manipulation is like nuclear fusion while the SENS-damage approach is like playing with fire. That may well be, but if playing with fire can saves some lives up until the time (could be a long time) we can safely manipulate metabolic pathways with skill, then it is certainly worth pursuing.
