ICCMSB 2012 - International Conference on Computational and Molecular Systems Biology (ICCMSB 2012)

The VIII. International Conference on C 194 omputational and Molecular Systems Biology is the premier forum for the presentation of new advances and research results in the fields of Computational and Molecular Systems Biology. The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world. Topics of interest for submission include, but are not limited to:

Mathematical and Molecular Systems Biology
Mathematical modeling and simulation of biosystems and their evolution
Functional genomics and proteomics
Identification and anal 195 ysis of gene regulatory networks
Identification and analysis of protein-protein interaction networks
Identification and analysis of metabolic networks
Computational approaches to complex genetic diseases
Synthetic biology and circuitry
Re-engineering and syn 194 thesis of biological systems and networks
Definition and study of theoretical properties of biologically-inspired formal languages
Qualitative and quantitative languages and calculi
Theoretical comparisons between different formal models of cellular processes
Models including symbo 194 lic evolution and learning
Spatial, multi-level, and multi-formalism modeling
Imulation and analysis methods for computational biology
Biologically-inspired extensions to concurrency theory, constraint programming, logical methods or language equivalences
Emergence of properties in comp 195 lex biological systems
Parallel, distributed, and multi-resolution simulation methods
Methods to predict biological network behavior from incomplete information
Modelling, analysis and simulation tools
Differential, discrete and/or stochastic modeling-language frameworks
194 Visualization methods for computational biology
Biological databases and exchange formats for biological data and standards
Detailed biological case-studies on which formal models successfully apply
Computer models in nano-sciences applied to biological domains
Model-driven 1a8 analysis of biological systems
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