{ "item_title" : "Computational Methods in Systems Biology", "item_author" : [" Luca Bortolussi", "Guido Sanguinetti "], "item_description" : "Regular Papers.- Sequential Reprogramming of Boolean Networks Made Practical.- Sequential Reprogramming of Biological Network Fate.- Control Variates for Stochastic Simulation of Chemical Reaction Networks.- Effective computational methods for hybrid stochastic gene networks.- On Chemical Reaction Network Design by a Nested Evolution Algorithm.- Designing Distributed Cell Classifier Circuits using a Genetic Algorithm.- Investigating a Hodgkin-Huxley type model for Drosophila larval neuromuscular junctions via particle swarm fitting.- Cell volume distributions in exponentially growing populations.- Transient Memory in Gene Regulation.- A Logic-Based Learning Approach to Explore Diabetes Patient Behaviors.- Reachability design through Approximate Bayesian Computation.- Fast enumeration of non-isomorphic chemical reaction networks.- A large-scale assessment of exact model reduction in the BioModels repository.- Computing Difference Abstractions of Metabolic Networks Under Kinetic Constraints.- Tool Papers.- BRE: IN - A Backend for Reasoning about Interaction Networks with Temporal Logic.- The Kappa simulator made interactive.- Biochemical reaction networks with fuzzy kinetic parameters in Snoopy.- Compartmental Modeling Software: a fast, discrete stochastic framework for biochemical and epidemiological simulation.- Spike - reproducible simulation experiments with configuration file branching.- KAMIStudio: an environment for biocuration of cellular signalling knowledge.- A new version of DAISY to test structural identifiability of biological models.- Extended Abstracts (Posters and Highlight Talks).- Semi-Quantitative Abstraction and Analysis of Chemical Reaction Networks.- Bayesian parameter estimation for stochastic reaction networks from steady-state observations.- Wasserstein Distances for Estimating Parameters in Stochastic Reaction Networks.- On Inferring Reactions from Data Time Series by a Statistical Learning Greedy Heuristics.- Barbaric Robustness Monitoring Revisited for STL* in Parasim.- Symmetry breaking for GATA-1/PU.1 model.- Scalable Control of Asynchronous Boolean Networks.- Transcriptional response of SK-N-AS cells to methamidophos (Extended Abstract).- Separators for polynomial dynamic systems with linear complexity.- Bounding First Passage Times in Chemical Reaction Networks.- Data-informed parameter synthesis for population Markov chains", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/03/031/303/3030313034_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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