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[PYHWK14a] N. Paoletti, B. Yordanov, Y. Hamadi, C.M. Wintersteiger, and H. Kugler. Analyzing and Synthesizing Genomic Logic Functions. In Proc. 26th International Conference on Computer Aided Verification (CAV), volume 8559 of LNCS, pages 343-357, Springer. 2014. [pdf] [bib]
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Notes: The original publication is available at: http://research.microsoft.com/apps/pubs/?id+226237 The original publication is available at www.springerlink.com.
Abstract. Deciphering the development program of an embryo is a fundamental question in biology. Landmark papers have recently shown how computational models of gene regulatory networks provide system-level casual understanding of the development processes of the sea urchin, and enable powerful predictive capabilities. A crucial aspect of the work is empirically deriving plausible models that explain all the known experimental data, a task that becomes infeasible in practice due to the inherent complexity of the biological systems. We present a generic Satisfiability Modulo Theories based approach to analyse and synthesize data constrained models. We apply our approach to the sea urchin embryo, and successfully improve the state-of-the-art by synthesizing, for the first time models that explain all the experimental observations. A strength of the proposed approach is the combination of accurate synthesis procedures for deriving biologically plausible models with the ability to prove inconsistency results, showing that for a given set of experiments and possible class of models no solution exists, and thus enabling practical refutation of biological models.