From the reviews: "This volume is the first of three planned books exploring the various tools used by the scientific community to deal with complexity in subjects such as big data, nonlinearity, and hidden interactions in systems biology. ... welcomed by readers ... who are directly or indirectly involved in the dynamic field of systems biology. The book offers insightful connections, knowledge that is often overlooked, and well-thought-out reasoning." (Adrian Pasculescu, Computing Reviews, January, 2014)

• Functional genomics, proteomics, metabolomics and bioinformatics for systems biology.- Comparing biological networks: a survey on graph classifying techniques.- Emergent properties of gene regulatory networks – models and data.- Regulatory crosstalk analysis of biochemical networks in the nucleus accumbens.- Properties of biological networks.- Network analysis for systems biology.- Computational approaches for reconstruction of time-varying biological networks from Omics data.- Probabilistic graphical modeling in systems biology: a framework for integrative approaches.- Innovations of the rule-based modeling approach.- Reproducibility of model-based results in systems biology.- Parameter identifiability and redundancy, with applications to a general class of stochastic carcinogenesis models.- Semantic systems biology: formal knowledge representation in systems biology for model construction, retrieval, validation and discovery.- Computational infrastructures for data and knowledge management in systems biology.- Computational tools and resources for integrative modeling in systems biology.- Agent-based modeling approaches to multi-scale systems biology: An example agent-based model of acute pulmonary inflammation.- Reconstructing cellular signaling and regulatory networks - an integrative approach for systems-level drug discovery.- A survey of current integrative network algorithms for systems biology.- Direct Computer Mapping based modeling of a multiscale process, involving p53/miR-34a signaling.

From the reviews: "This volume is the first of three planned books exploring the various tools used by the scientific community to deal with complexity in subjects such as big data, nonlinearity, and hidden interactions in systems biology. ... welcomed by readers ... who are directly or indirectly involved in the dynamic field of systems biology. The book offers insightful connections, knowledge that is often overlooked, and well-thought-out reasoning." (Adrian Pasculescu, Computing Reviews, January, 2014)

• Functional genomics, proteomics, metabolomics and bioinformatics for systems biology.- Comparing biological networks: a survey on graph classifying techniques.- Emergent properties of gene regulatory networks – models and data.- Regulatory crosstalk analysis of biochemical networks in the nucleus accumbens.- Properties of biological networks.- Network analysis for systems biology.- Computational approaches for reconstruction of time-varying biological networks from Omics data.- Probabilistic graphical modeling in systems biology: a framework for integrative approaches.- Innovations of the rule-based modeling approach.- Reproducibility of model-based results in systems biology.- Parameter identifiability and redundancy, with applications to a general class of stochastic carcinogenesis models.- Semantic systems biology: formal knowledge representation in systems biology for model construction, retrieval, validation and discovery.- Computational infrastructures for data and knowledge management in systems biology.- Computational tools and resources for integrative modeling in systems biology.- Agent-based modeling approaches to multi-scale systems biology: An example agent-based model of acute pulmonary inflammation.- Reconstructing cellular signaling and regulatory networks - an integrative approach for systems-level drug discovery.- A survey of current integrative network algorithms for systems biology.- Direct Computer Mapping based modeling of a multiscale process, involving p53/miR-34a signaling.

From the reviews: "This volume is the first of three planned books exploring the various tools used by the scientific community to deal with complexity in subjects such as big data, nonlinearity, and hidden interactions in systems biology. ... welcomed by readers ... who are directly or indirectly involved in the dynamic field of systems biology. The book offers insightful connections, knowledge that is often overlooked, and well-thought-out reasoning." (Adrian Pasculescu, Computing Reviews, January, 2014)

• Functional genomics, proteomics, metabolomics and bioinformatics for systems biology.- Comparing biological networks: a survey on graph classifying techniques.- Emergent properties of gene regulatory networks – models and data.- Regulatory crosstalk analysis of biochemical networks in the nucleus accumbens.- Properties of biological networks.- Network analysis for systems biology.- Computational approaches for reconstruction of time-varying biological networks from Omics data.- Probabilistic graphical modeling in systems biology: a framework for integrative approaches.- Innovations of the rule-based modeling approach.- Reproducibility of model-based results in systems biology.- Parameter identifiability and redundancy, with applications to a general class of stochastic carcinogenesis models.- Semantic systems biology: formal knowledge representation in systems biology for model construction, retrieval, validation and discovery.- Computational infrastructures for data and knowledge management in systems biology.- Computational tools and resources for integrative modeling in systems biology.- Agent-based modeling approaches to multi-scale systems biology: An example agent-based model of acute pulmonary inflammation.- Reconstructing cellular signaling and regulatory networks - an integrative approach for systems-level drug discovery.- A survey of current integrative network algorithms for systems biology.- Direct Computer Mapping based modeling of a multiscale process, involving p53/miR-34a signaling.