Titlebook: Logic Synthesis for Genetic Diseases; Modeling Disease Beh Pey-Chang Kent Lin,Sunil P. Khatri Book 2014 Springer Science+Business Media New

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Determining Gene Function in Boolean Networks using SAT a multitude of GRNs may satisfy the observed behavior, yielding a reduced certainty in the final result due to lack of data. We will also study the behavior of the number of satisfying GRNs with respect to the number of observations ..

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del the genetic disease behavior as a BN, with powerful implicit enumeration techniques. Coverage also includes techniques from VLSI testing to control a faulty BN, transforming its behavior to a healthy BN, potentially aiding in efforts to find the best candidates for treatment of genetic diseases.978-1-4939-5535-0978-1-4614-9429-4

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emonstrates how techniques such as Boolean Satisfiability (SThis book brings to bear a body of logic synthesis techniques, in order to contribute to the analysis and control of Boolean Networks (BN) for modeling genetic diseases such as cancer. The authors provide several VLSI logic techniques to mo

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Predictor Set Inference using SATach CNF is solved using a SAT solver to find candidate predictor sets. Statistical analysis of the resulting predictor sets selects the most likely predictor set of the GRN, corresponding to the attractor data. We demonstrate our algorithm on attractor state data from a melanoma study and present our predictor set results.

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