The trans-NIH Biomedical Information Science and Technology Initiative (BISTI) funds a range of projects that advance computer science and technology to address problems in biology and medicine. BISTI, which is led by NIGMS, has just reissued four broad-based program announcements to support “innovations in biomedical computing.” In the past, BISTI has awarded 198 of these grants ranging from $200,000 to $3 million.
The announcements cover traditional research projects; exploratory, high-risk/high-impact projects; small business innovation research; and small business technology transfer grants. They apply to most areas of NIH research, from basic to clinical, and require that more than 50 percent of the proposed research involve computing. For example, investigators can request funds for scientists and software personnel to develop models to analyze a disease, and they can also request funds to obtain data or perform experiments to validate the models. Again, in all cases the majority of effort should be on the computing side.
If you want to significantly expand your computing efforts and capabilities, these funding announcements are a really great opportunity!
The BISTI initiative has had a tremendous impact in biomedicine. Bioinformatics and computational biology have become the equivalent of what molecular biology was at its inception, i.e. these are accepted as an integral part of mainstream biology.
Now may be appropriate time for transitioning BISTI into phase II, where there is tight integration between experimental biomedicine and computational biology. Areas of systems biology dealing with mammalian systems, be they cells, tissues, organs or whole organisms may be excellent choices for explicit mention in RFAs and in parallel getting researchers who are truly multidisciplinary involved in review process would benefit the future.
It should be argued that “purely computational” aspects such as abstract theoretical explorations in biology, have only had marginal success and conversely there persists a tendency in part to dismiss a lot of computation as being irrelevant. Both need to be avoided. One way to frame the importance of the integration between computational and experimental biomedicine arises from a notion of “models”. It is traditional for biologists to form conceptual models be they mechanistic or quantitiative and molecular or larger. Today with the advent of high throughput biology it is possible to develop models that are both data and biologically inspired and are amenable to computation.
Such an engineering perspective could well be the driver of next generation “BISTI” initiatives.