Elements of Computational Systems Biology

HUMA M. LODHI, PhD, MBCS, is a researcher with the Department of Computing, Imperial College London. She has studied at Royal Holloway, University of London and has previously worked as a researcher with the Department of Computer Science, University of Sheffield. STEPHEN H. MUGGLETON, PhD, FAAAI, is a Professor of Machine Learning, Department of Computing, Imperial College London, and is the Director of Modeling, BBSRC Centre for Integrative Systems Biology, Imperial College London. He is a Fellow of the American Association for Artificial Intelligence and was a professor of machine learning, Department of Computing, University of York.Both editors have published in leading international conferences and journals.

“The book should serve well as a resource for anyone interested in learning about computational systems biology.”  (The Quarterly Review of Biology, 1 March 2012)

• Preface. Contributors.PART I: OVERVIEW.1 Advances in Computational Systems Biology (Huma M. Lodhi).PART II: BIOLOGICAL NETWORK MODELING.2 Models in Systems Biology: The Parameter Problem and the Meanings of Robustness (Jeremy Gunawardena).3 In Silico Analysis of Combined Therapeutics Strategy for Hearth Failure (Sung-Young Shin, Tae-Hwan Kim, Kwang-Hyun Cho, and Sang-Mok Choo).4 Rule-Based Modeling and Model Refinement (Elaine Murphy, Vincent Danos, Jerome Feret, Jean Krivine, and Russell Harmer).5 A (Natural) Computing Perspective on Cellular Processes (Mateo Cavaliere and Tommaso Mazza).6 Simulating Filament Dynamics in Cellular Systems (Wilbur E. Channels and Pablo A. Iglesias).PART III: BIOLOGICAL NETWORK INFERENCE.7 Reconstruction of Biological Networks by Supervised Machine Learning Approaches (Jean-Philippe Vert).8 Supervised Inference of Metabolic Networks from the Integration of Genomic Data and Chemical Information (Yoshihiro Yamanishi).9 Integrating Abduction and Induction in Biological Inference Using CF-Induciton (Yoshitaka Yamamoto, Katsumi Inoue, and Andrei Doncescu).10 Analysis and Control of Deterministic and Probabilistic Boolean Networks (Tatsuya Akutsu and Wai-Ki Ching).11 Probabilistic Methods and Rate Heterogeneity (Tal Pupko and Itay Mayrose).PART IV: GENOMICS AND COMPUTATIONAL SYSTEMS BIOLOGY.12 From DNA Motifs to Gene Networks: A Review of Physical Interaction Models (Panayiotis V. Benos and Alain B. Tchagang).13 The Impact of Whole Genome In Silico Screening for Nuclear Receptor-Binding Sites in Systems Biology (Carsten Carlberg and Merja Heinaniemi).14 Environmental and Physiological Insights from Microbial Genome Sequences (Alessandra Carbone and Anthony Mathelier).PART V: SOFTWARE TOOLS FOR SYSTEMS BIOLOGY.15 Ali Baba: A Text Mining Tool for Systems Biology (Jorg Hakenberg, Conrad Plake, and Ulf Leser).16 Validation Issues in Regulatory Module Discovery (Alok Mishra and Duncan Gillies).17 Computational Imaging and Modeling for Systems Biology (Ling-Yun Wu, Xiaobo Zhou, and Stephen T.C. Wong).Index.Series Information.