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Titlebook: Computational Methods in Systems Biology; 19th International C Eugenio Cinquemani,Loïc Paulevé Conference proceedings 2021 Springer Nature

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楼主: ISH
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Population Design for Synthetic Gene Circuits,le, biomedical or industrial applications. Computer-aided design methods have been developed to help choose appropriate network structures and biological parts for a given design objective. However, they almost always model the behavior of the network in an average cell, despite pervasive cell-to-ce
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Protein Noise and Distribution in a Two-Stage Gene-Expression Model Extended by an mRNA Inactivatioll level. Mathematical modelling of this stochastic phenomenon enables us to elucidate the underlying molecular mechanisms quantitatively. Here we present a two-stage stochastic gene expression model that extends the standard model by an mRNA inactivation loop. The extended model exhibits smaller pr
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LNetReduce: Tool for Reducing Linear Dynamic Networks with Separated Timescales,ers. Such models describe deterministic or stochastic monomolecular chemical reaction networks, but also random walks on weighted protein-protein interaction networks, spreading of infectious diseases and opinion in social networks, communication in computer networks. The reduced network is obtained
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BioFVM-X: An MPI+OpenMP 3-D Simulator for Biological Systems,at solves diffusive transport Partial Differential Equations for 3-D biological simulations successfully applied to tissue and cancer biology problems. Currently, BioFVM is only shared-memory parallelized using OpenMP, greatly limiting the execution of large-scale jobs in HPC clusters. We present Bi
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Intelligence and Intelligence Testing,an alternative semantics that propagates values from one occurrence of a variable to other ones, and show that this novel approach permits a more efficient pattern matching algorithm. We confirm this theoretical result by benchmarking proof-of-concept implementations of both approaches.
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Mila Schwartz,Victor Moin,Manal Klayleady-state distribution of active and inactive mRNA and protein species. We determine its generating function and derive a recursive formula for the protein distribution. The results of the analytical formula are cross-validated by kinetic Monte-Carlo simulation.
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