The University of Chicago Research Funding

• Principal Investigator: Andrey Rzhetsky, PhD, Professor, Committee on Genetics, Genomics & Systems Biology, Human Genetics, Institute for Genomics & Systems Biology, Computation Institute
• Start Date: June 1, 2009
• Total Award Amount: $603,044 (first year) $607,996 (second year)

Public Health Relevance

Every field of modern biomedicine hosts a rich plurality of theoretical views but most remain unknown to the majority, eclipsed by a dominant perspective that disproportionately attracts funds, journal page-space, and attention. This often unwarranted narrowness of focus is particularly disturbing in fields devoted to the biology and cure of complex maladies such as autism, schizophrenia, diabetes, and breast cancer, where a multiplicity of genetic and environmental influences likely play a role. We propose the development of a system for harvesting, synthesizing, formalizing, and comparatively testing diverse, competing, and oft- unpublished hypotheses that will dramatically improve the odds and speed of theory development, even without explicitly demanding more experimental resources.

Project Description

Our hypothesis is that we can drastically accelerate scientific discovery by collecting and making visible, comparable, and computable hypotheses, hunches, and theory-specific evidence beyond the dominant paradigm(s) of the field. Accordingly, we propose a multidisciplinary approach to harvest, formalize and compute over hypotheses and findings produced within any scientific community.

Our approach unfolds in a four-stage cycle: 1) Search for scientific hunches and findings from diverse sources across the scientific community; 2) Synthesize new hypotheses given prior findings and ideas and Formalize them into a composite reasoning model; 3) Compute the probability of each hypothesis, given published statements and unpublished observations; 4) Disseminate findings, hypotheses, and their certainties back to the scientific community in compelling ways that stimulate scientific engagement and advance.

This award is funded under the American Recovery and Reinvestment Act of 2009, NIH Award number: 1R01LM010132-01