Computational Analysis Of Biochemical Systems
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Computational Analysis of Biochemical Systems
Author | : Eberhard O. Voit |
Publsiher | : Cambridge University Press |
Total Pages | : 556 |
Release | : 2000-09-04 |
Genre | : Medical |
ISBN | : 0521785790 |
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Teaches the use of modern computational methods for the analysis of biomedical systems using case studies and accompanying software.
Stochastic Analysis of Biochemical Systems
Author | : David F. Anderson,Thomas G. Kurtz |
Publsiher | : Springer |
Total Pages | : 84 |
Release | : 2015-04-23 |
Genre | : Mathematics |
ISBN | : 9783319168951 |
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This book focuses on counting processes and continuous-time Markov chains motivated by examples and applications drawn from chemical networks in systems biology. The book should serve well as a supplement for courses in probability and stochastic processes. While the material is presented in a manner most suitable for students who have studied stochastic processes up to and including martingales in continuous time, much of the necessary background material is summarized in the Appendix. Students and Researchers with a solid understanding of calculus, differential equations and elementary probability and who are well-motivated by the applications will find this book of interest. David F. Anderson is Associate Professor in the Department of Mathematics at the University of Wisconsin and Thomas G. Kurtz is Emeritus Professor in the Departments of Mathematics and Statistics at that university. Their research is focused on probability and stochastic processes with applications in biology and other areas of science and technology. These notes are based in part on lectures given by Professor Anderson at the University of Wisconsin – Madison and by Professor Kurtz at Goethe University Frankfurt.
Computer Applications in Biotechnology 2004
Author | : Marie-Noelle Pons,Jan Van Impe |
Publsiher | : Elsevier |
Total Pages | : 610 |
Release | : 2005-08-02 |
Genre | : Science |
ISBN | : 008044251X |
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Computational Modeling of Biological Systems
Author | : Nikolay V Dokholyan |
Publsiher | : Springer Science & Business Media |
Total Pages | : 360 |
Release | : 2012-02-12 |
Genre | : Science |
ISBN | : 9781461421450 |
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Computational modeling is emerging as a powerful new approach to study and manipulate biological systems. Multiple methods have been developed to model, visualize, and rationally alter systems at various length scales, starting from molecular modeling and design at atomic resolution to cellular pathways modeling and analysis. Higher time and length scale processes, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. This book provides an overview of the established computational methods used for modeling biologically and medically relevant systems.
Computational Systems Biology
Author | : Andres Kriete,Roland Eils |
Publsiher | : Academic Press |
Total Pages | : 548 |
Release | : 2013-11-26 |
Genre | : Computers |
ISBN | : 9780124059382 |
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This comprehensively revised second edition of Computational Systems Biology discusses the experimental and theoretical foundations of the function of biological systems at the molecular, cellular or organismal level over temporal and spatial scales, as systems biology advances to provide clinical solutions to complex medical problems. In particular the work focuses on the engineering of biological systems and network modeling. Logical information flow aids understanding of basic building blocks of life through disease phenotypes Evolved principles gives insight into underlying organizational principles of biological organizations, and systems processes, governing functions such as adaptation or response patterns Coverage of technical tools and systems helps researchers to understand and resolve specific systems biology problems using advanced computation Multi-scale modeling on disparate scales aids researchers understanding of dependencies and constraints of spatio-temporal relationships fundamental to biological organization and function.
Elements of Computational Systems Biology
Author | : Huma M. Lodhi,Stephen H. Muggleton |
Publsiher | : John Wiley & Sons |
Total Pages | : 435 |
Release | : 2010-03-25 |
Genre | : Computers |
ISBN | : 9780470556740 |
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Groundbreaking, long-ranging research in this emergent field that enables solutions to complex biological problems Computational 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. Offers a coordinated integrated systems view of defining and applying computational and mathematical tools and methods to solving problems in systems biology Chapters 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 Helps reduce the gap between mathematics and biology by presenting chapters on mathematical models of biological systems Establishes solutions in computer science, biology, chemistry, and physics by presenting an in-depth description of computational methodologies for systems biology Elements 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.
Computational Systems Biology
Author | : Paola Lecca,Angela Re,Adaoha Elizabeth Ihekwaba,Ivan Mura,Thanh-Phuong Nguyen |
Publsiher | : Woodhead Publishing |
Total Pages | : 180 |
Release | : 2016-07-29 |
Genre | : Science |
ISBN | : 9780081001158 |
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Computational Systems Biology: Inference and Modelling provides an introduction to, and overview of, network analysis inference approaches which form the backbone of the model of the complex behavior of biological systems. This book addresses the challenge to integrate highly diverse quantitative approaches into a unified framework by highlighting the relationships existing among network analysis, inference, and modeling. The chapters are light in jargon and technical detail so as to make them accessible to the non-specialist reader. The book is addressed at the heterogeneous public of modelers, biologists, and computer scientists. Provides a unified presentation of network inference, analysis, and modeling Explores the connection between math and systems biology, providing a framework to learn to analyze, infer, simulate, and modulate the behavior of complex biological systems Includes chapters in modular format for learning the basics quickly and in the context of questions posed by systems biology Offers a direct style and flexible formalism all through the exposition of mathematical concepts and biological applications
Computational Methods in Systems Biology
Author | : Pierpaolo Degano,Roberto Gorrieri |
Publsiher | : Springer Science & Business Media |
Total Pages | : 337 |
Release | : 2009-08-17 |
Genre | : Computers |
ISBN | : 9783642038440 |
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This book constitutes the refereed proceedings of the 7th International Conference on Computational Methods in Systems Biology, CMSB 2009, held in Bologna, Italy, August 31 - September 1, 2009. The 18 revised full papers presented together with the summaries of 3 invited papers were carefully reviewed and selected from more than 45 submissions. The papers cover theoretical or applied contributions that are motivated by a biological question focusing on modeling approaches, including process algebra, simulation approaches, analysis methods, in particular model checking and flux analysis, and case studies.