{"product_id":"elements-of-computational-systems-biology-hardback-9780470180938","title":"Elements of Computational Systems Biology (Hardback) 9780470180938","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eElements of Computational Systems Biology\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eHuma M. Lodhi (Edited by), HM Lodhi (Author), Stephen H. Muggleton (Edited by), Yi Pan (Series edited by), Albert Y. Zomaya (Series edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780470180938, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 5 March 2010\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e434 pages\u003cbr\u003e24.4 x 16.3 x 2.9 cm, 0.767 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e“The book should serve well as a resource for anyone interested in learning about computational systems biology.”  (\u003ci\u003eThe Quarterly Review of Biology\u003c\/i\u003e, 1 March 2012)\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003eGroundbreaking, long-ranging research in this emergent field that enables solutions to complex biological problems\u003c\/p\u003e \u003cp\u003eComputational systems biology is an emerging discipline that is evolving quickly due to recent advances in biology such as genome sequencing, high-throughput technologies, and the recent development of sophisticated computational methodologies. Elements of Computational Systems Biology is a comprehensive reference covering the computational frameworks and techniques needed to help research scientists and professionals in computer science, biology, chemistry, pharmaceutical science, and physics solve complex biological problems. Written by leading experts in the field, this practical resource gives detailed descriptions of core subjects, including biological network modeling, analysis, and inference; presents a measured introduction to foundational topics like genomics; and describes state-of-the-art software tools for systems biology.\u003c\/p\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eOffers a coordinated integrated systems view of defining and applying computational and mathematical tools and methods to solving problems in systems biology\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eChapters provide a multidisciplinary approach and range from analysis, modeling, prediction, reasoning, inference, and exploration of biological systems to the implications of computational systems biology on drug design and medicine\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eHelps reduce the gap between mathematics and biology by presenting chapters on mathematical models of biological systems\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eEstablishes solutions in computer science, biology, chemistry, and physics by presenting an in-depth description of computational methodologies for systems biology\u003c\/p\u003e \u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eElements of Computational Systems Biology is intended for academic\/industry researchers and scientists in computer science, biology, mathematics, chemistry, physics, biotechnology, and pharmaceutical science. It is also accessible to undergraduate and graduate students in machine learning, data mining, bioinformatics, computational biology, and systems biology courses.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePreface.  \u003cp\u003eContributors.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART I: OVERVIEW.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1 Advances in Computational Systems Biology (\u003ci\u003eHuma M. Lodhi\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART II: BIOLOGICAL NETWORK MODELING.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2 Models in Systems Biology: The Parameter Problem and the Meanings of Robustness (\u003ci\u003eJeremy Gunawardena\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e3 In Silico Analysis of Combined Therapeutics Strategy for Hearth Failure (\u003ci\u003eSung-Young Shin, Tae-Hwan Kim, Kwang-Hyun Cho, and Sang-Mok Choo\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e4 Rule-Based Modeling and Model Refinement (\u003ci\u003eElaine Murphy, Vincent Danos, Jerome Feret, Jean Krivine, and Russell Harmer\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e5 A (Natural) Computing Perspective on Cellular Processes (\u003ci\u003eMateo Cavaliere and Tommaso Mazza\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e6 Simulating Filament Dynamics in Cellular Systems (\u003ci\u003eWilbur E. Channels and Pablo A. Iglesias\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART III: BIOLOGICAL NETWORK INFERENCE.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7 Reconstruction of Biological Networks by Supervised Machine Learning Approaches (\u003ci\u003eJean-Philippe Vert\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e8 Supervised Inference of Metabolic Networks from the Integration of Genomic Data and Chemical Information (\u003ci\u003eYoshihiro Yamanishi\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e9 Integrating Abduction and Induction in Biological Inference Using CF-Induciton (\u003ci\u003eYoshitaka Yamamoto, Katsumi Inoue, and Andrei Doncescu\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e10 Analysis and Control of Deterministic and Probabilistic Boolean Networks (\u003ci\u003eTatsuya Akutsu and Wai-Ki Ching\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e11 Probabilistic Methods and Rate Heterogeneity (\u003ci\u003eTal Pupko and Itay Mayrose\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART IV: GENOMICS AND COMPUTATIONAL SYSTEMS BIOLOGY.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12 From DNA Motifs to Gene Networks: A Review of Physical Interaction Models (\u003ci\u003ePanayiotis V. Benos and Alain B. Tchagang\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e13 The Impact of Whole Genome \u003ci\u003eIn Silico\u003c\/i\u003e Screening for Nuclear Receptor-Binding Sites in Systems Biology (\u003ci\u003eCarsten Carlberg and Merja Heinaniemi\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e14 Environmental and Physiological Insights from Microbial Genome Sequences (\u003ci\u003eAlessandra Carbone and Anthony Mathelier\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART V: SOFTWARE TOOLS FOR SYSTEMS BIOLOGY.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15 Ali Baba: A Text Mining Tool for Systems Biology (\u003ci\u003eJorg Hakenberg, Conrad Plake, and Ulf Leser\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e16 Validation Issues in Regulatory Module Discovery (\u003ci\u003eAlok Mishra and Duncan Gillies\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e17 Computational Imaging and Modeling for Systems Biology (\u003ci\u003eLing-Yun Wu, Xiaobo Zhou, and Stephen T.C. Wong\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e \u003cp\u003eSeries Information.\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Biology, life sciences [\u003ca title=\"See our other books on Biology, life sciences\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Biology,%20life%20sciences%20%5BPS%5D%22\"\u003ePS\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand New","offer_id":52257150828824,"sku":"9780470180938","price":94.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9780470180938.jpg?v=1781277654","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/elements-of-computational-systems-biology-hardback-9780470180938","provider":"Freshly Printed Books","version":"1.0","type":"link"}