Computational Methods in Systems Biology : 10th International Conference, CMSB 2012, London, UK, October 3-5, 2012. Proceedings
This book constitutes the thoroughly refereed conference proceedings of the 10th International Conference on Computational Methods in Systems Biology, CMSB 2012, held in London, UK, during October 3-5, 2012. The 17 revised full papers and 8 flash posters presented together with the summaries of 3 in...
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Auteurs principaux : | , |
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Format : | Livre |
Langue : | anglais |
Titre complet : | Computational Methods in Systems Biology : 10th International Conference, CMSB 2012, London, UK, October 3-5, 2012. Proceedings / edited by David Gilbert, Monika Heiner. |
Publié : |
Berlin, Heidelberg :
Springer Berlin Heidelberg
, 2012 Cham : Springer Nature |
Collection : | Lecture notes in bioinformatics (Online) ; 7605 |
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Computational Methods in Systems Biology Autre format: Computational Methods in Systems Biology |
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330 | |a This book constitutes the thoroughly refereed conference proceedings of the 10th International Conference on Computational Methods in Systems Biology, CMSB 2012, held in London, UK, during October 3-5, 2012. The 17 revised full papers and 8 flash posters presented together with the summaries of 3 invited papers were carefully reviewed and selected from 62 submissions. The papers cover the analysis of biological systems, networks, and data ranging from intercellular to multiscale. Topics included high-performance computing, and for the first time papers on synthetic biology. | ||
359 | 1 | |a Differential and Integral Views of Gene-Phenotype Relations -- Resolving the Three-Dimensional Histology of the Heart -- Bimodal Protein Distributions in Heterogeneous Oscillating Systems -- Expressive Statistical Model Checking of Genetic Networks with Delayed Stochastic Dynamics -- Detection of Multi-clustered Genes and Community Structure for the Plant Pathogenic Fungus -- Analysis of Modular Organization of Interaction Networks Based on Asymptotic Dynamics -- Concretizing the Process Hitting into Biological Regulatory Networks -- Investigating Co-infection Dynamics through Evolution of Bio-PEPA Model Parameters: A Combined Process Algebra and Evolutionary Computing Approach -- Population Dynamics P Systems on CUDA -- Efficient Handling of Large Signaling-Regulatory Networks by Focusing on Their Core Control -- Simulating Insulin Infusion Pump Risks by In-Silico Modeling of the Insulin-Glucose Regulatory System -- Revisiting the Training of Logic Models of Protein Signaling Networks with a Formal Approach Based on Answer Set Programming. | |
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