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Reachability Analysis and Revision of Dynamics of Biological Regulatory Networks

Abstract : Concurrent systems become a good choice to fit the data and analyze the underlying mechanics for their simple but expressive semantics. However, learning and analyzing such concurrent systems are computationally difficult. When dealing with big data sets, the state-of-the-art techniques appear to be insufficient, either in term of efficiency or in term of precision. In this thesis, we propose a refined modeling framework ABAN (Asynchronous Binary Automata Network) and develop reachability analysis techniques based on ABAN: PermReach (Reachability via Permutation search) and ASPReach (Reachability via Answer Set Programming). Then we propose two model learning/constructing methods: CRAC (Completion via Reachability And Correlations) and M2RIT (Model Revision via Reachability and Interpretation Transitions) using continuous and discrete data to fit the model and using reachability properties to constrain the output models.
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Submitted on : Wednesday, December 18, 2019 - 5:24:09 PM
Last modification on : Wednesday, January 19, 2022 - 3:48:23 PM


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  • HAL Id : tel-02145438, version 2


Xinwei Chai. Reachability Analysis and Revision of Dynamics of Biological Regulatory Networks. Bioinformatics [q-bio.QM]. École centrale de Nantes, 2019. English. ⟨NNT : 2019ECDN0014⟩. ⟨tel-02145438v2⟩



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