The greatest difficulties in biomedical research are that it takes too long, and that it costs too much. Evaluating economic tradeoffs between proposed experiments is possible using well-studied optimization techniques from operations research, and if we could simultaneously evaluate the scientific merit and potential impact of the proposed experiments as part of the same optimization process, we could more quickly and easily make intelligent and efficient decisions about experimental planning.
In prior work funded by NSF, we developed the Hypothesis-Space Browser, a “tool for thought” that evaluates and organizes competing biological hypotheses on the basis of how strongly they are supported by, or contradict, the statements made by the available data. For this proposal, we are reformulating the Contradiction-Based Logic that underlies the Hypothesis-Space Browser to recast hypothesis evaluation in terms of an optimization problem. The motivation of our research is to enable hypothesis analysis to be carried out in the same domain as risk vs. reward optimization, even in the presence of contradictory or inconsistent data.
This project is funded by a Seed Grant for Exploratory Research from NSF.