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A Contradiction-Based Framework for Testing Gene Regulation Hypotheses
Stanford, California August 11-August 14
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSB.2003.1227430IEEE Computer Society Bioinformatics ...
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Steve Racunas, The Pennsylvania State University
Nigam Shah, The Pennsylvania State University
Nina V. Fedoroff, The Pennsylvania State University
We have developed a mathematical framework for representing and testing hypotheses about gene, protein, and signaling molecule interactions. It takes a hierarchical, contradiction-based approach, and can make use of multiple data sources to assess hypothesis viability and to generate a viability partial order over the space of hypotheses. We have developed an event-based formal language for the expression of such hypotheses. This language seamlessly integrates regulatory diagrams (graphical inputs) and structured English (text input) to maximize flexibility. We have developed a pre-topological formalism that allows us to make precise statements about hypothesis similarity and the convergence of iterative refinements of a base hypothesis. To this, we add mathematical machinery that allows us to make precise statements about control and regulation.
Citation:
Steve Racunas, Nigam Shah, Nina V. Fedoroff, "A Contradiction-Based Framework for Testing Gene Regulation Hypotheses," csb, pp.634, IEEE Computer Society Bioinformatics Conference (CSB'03), 2003
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