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Computational Methods in Systems Biology : 17th International Conference, CMSB 2019, Trieste, Italy, September 18-20, 2019, Proceedings / edited by Luca Bortolussi, Guido Sanguinetti.

SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online

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Format:
Book
Contributor:
Bortolussi, Luca, editor.
Sanguinetti, Guido, 1974- editor.
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
Lecture notes in computer science. Lecture notes in bioinformatics ; 11773.
Lecture Notes in Bioinformatics ; 11773
Language:
English
Subjects (All):
Bioinformatics.
Artificial intelligence.
Algorithms.
Logic, Symbolic and mathematical.
Computer science--Mathematics.
Computer science.
Software engineering.
Computational Biology/Bioinformatics.
Artificial Intelligence.
Algorithm Analysis and Problem Complexity.
Mathematical Logic and Formal Languages.
Mathematics of Computing.
Software Engineering/Programming and Operating Systems.
Local Subjects:
Computational Biology/Bioinformatics.
Artificial Intelligence.
Algorithm Analysis and Problem Complexity.
Mathematical Logic and Formal Languages.
Mathematics of Computing.
Software Engineering/Programming and Operating Systems.
Physical Description:
1 online resource (XI, 388 pages) : 487 illustrations, 87 illustrations in color.
Edition:
First edition 2019.
Contained In:
Springer eBooks
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2019.
System Details:
text file PDF
Summary:
This book constitutes the refereed proceedings of the 17th International Conference on Computational Methods in Systems Biology, CMSB 2019, held in Trieste, Italy, in September 2019. The 14 full papers, 7 tool papers and 11 posters were carefully reviewed and selected from 53 submissions. Topics of interest include formalisms for modeling biological processes; models and their biological applications; frameworks for model verification, validation, analysis, and simulation of biological systems; high-performance computational systems biology and parallel implementations; model inference from experimental data; model integration from biological databases; multi-scale modeling and analysis methods; computational approaches for synthetic biology; and case studies in systems and synthetic biology.
Contents:
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.
Other Format:
Printed edition:
ISBN:
978-3-030-31304-3
9783030313043
Access Restriction:
Restricted for use by site license.

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