Computational Systems Biology Of Cancer
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Computational Systems Biology Of Cancer
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Author : Emmanuel Barillot
language : en
Publisher: CRC Press
Release Date : 2012-08-25
Computational Systems Biology Of Cancer written by Emmanuel Barillot and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-25 with Science categories.
The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models—integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencing. Offering promising insights on how to defeat cancer, the emerging field of systems biology captures the complexity of biological phenomena using mathematical and computational tools. Novel Approaches to Fighting Cancer Drawn from the authors’ decade-long work in the cancer computational systems biology laboratory at Institut Curie (Paris, France), Computational Systems Biology of Cancer explains how to apply computational systems biology approaches to cancer research. The authors provide proven techniques and tools for cancer bioinformatics and systems biology research. Effectively Use Algorithmic Methods and Bioinformatics Tools in Real Biological Applications Suitable for readers in both the computational and life sciences, this self-contained guide assumes very limited background in biology, mathematics, and computer science. It explores how computational systems biology can help fight cancer in three essential aspects: Categorising tumours Finding new targets Designing improved and tailored therapeutic strategies Each chapter introduces a problem, presents applicable concepts and state-of-the-art methods, describes existing tools, illustrates applications using real cases, lists publically available data and software, and includes references to further reading. Some chapters also contain exercises. Figures from the text and scripts/data for reproducing a breast cancer data analysis are available at www.cancer-systems-biology.net.
Computational Systems Biology Of Cancer
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Author : Emmanuel Barillot
language : en
Publisher: CRC Press
Release Date : 2012-08-25
Computational Systems Biology Of Cancer written by Emmanuel Barillot and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-25 with Computers categories.
The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models-integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencin
Computational Biology Of Cancer
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Author : Dominik Wodarz
language : en
Publisher: World Scientific
Release Date : 2005
Computational Biology Of Cancer written by Dominik Wodarz and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Science categories.
- Provides an introduction to computational methods in cancer biology - Follows a multi-disciplinary approach
Systems Biology Of Cancer
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Author : Sam Thiagalingam
language : en
Publisher: Cambridge University Press
Release Date : 2015-04-09
Systems Biology Of Cancer written by Sam Thiagalingam and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-09 with Mathematics categories.
An overview of the current systems biology-based knowledge and the experimental approaches for deciphering the biological basis of cancer.
Computational Systems Biology
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Author : Andres Kriete
language : en
Publisher: Academic Press
Release Date : 2013-11-26
Computational Systems Biology written by Andres Kriete and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-26 with Science categories.
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.
Computational Systems Biology Approaches In Cancer Research
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Author : Inna Kuperstein
language : en
Publisher: CRC Press
Release Date : 2019-09-09
Computational Systems Biology Approaches In Cancer Research written by Inna Kuperstein and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-09 with Computers categories.
Praise for Computational Systems BiologyApproaches in Cancer Research: "Complex concepts are written clearly and with informative illustrations and useful links. The book is enjoyable to read yet provides sufficient depth to serve as a valuable resource for both students and faculty." — Trey Ideker, Professor of Medicine, UC Xan Diego, School of Medicine "This volume is attractive because it addresses important and timely topics for research and teaching on computational methods in cancer research. It covers a broad variety of approaches, exposes recent innovations in computational methods, and provides acces to source code and to dedicated interactive web sites." — Yves Moreau, Department of Electrical Engineering, SysBioSys Centre for Computational Systems Biology, University of Leuven With the availability of massive amounts of data in biology, the need for advanced computational tools and techniques is becoming increasingly important and key in understanding biology in disease and healthy states. This book focuses on computational systems biology approaches, with a particular lens on tackling one of the most challenging diseases - cancer. The book provides an important reference and teaching material in the field of computational biology in general and cancer systems biology in particular. The book presents a list of modern approaches in systems biology with application to cancer research and beyond. It is structured in a didactic form such that the idea of each approach can easily be grasped from the short text and self-explanatory figures. The coverage of topics is diverse: from pathway resources, through methods for data analysis and single data analysis to drug response predictors, classifiers and image analysis using machine learning and artificial intelligence approaches. Features Up to date using a wide range of approaches Applicationexample in each chapter Online resources with useful applications’
Cancer Bioinformatics
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Author : Ying Xu
language : en
Publisher: Springer
Release Date : 2014-08-30
Cancer Bioinformatics written by Ying Xu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-30 with Computers categories.
This book provides a framework for computational researchers studying the basics of cancer through comparative analyses of omic data. It discusses how key cancer pathways can be analyzed and discovered to derive new insights into the disease and identifies diagnostic and prognostic markers for cancer. Chapters explain the basic cancer biology and how cancer develops, including the many potential survival routes. The examination of gene-expression patterns uncovers commonalities across multiple cancers and specific characteristics of individual cancer types. The authors also treat cancer as an evolving complex system, explore future case studies, and summarize the essential online data sources. Cancer Bioinformatics is designed for practitioners and researchers working in cancer research and bioinformatics. It is also suitable as a secondary textbook for advanced-level students studying computer science, biostatistics or biomedicine.
Microrna Cancer Regulation
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Author : Ulf Schmitz
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-02-03
Microrna Cancer Regulation written by Ulf Schmitz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-03 with Medical categories.
This edited reflects the current state of knowledge about the role of microRNAs in the formation and progression of solid tumours. The main focus lies on computational methods and applications, together with cutting edge experimental techniques that are used to approach all aspects of microRNA regulation in cancer. We are sure that the emergence of high-throughput quantitative techniques will make this integrative approach absolutely necessary in the near future. This book will be a resource for researchers starting out with cancer microRNA research, but is also intended for the experienced researcher who wants to incorporate concepts and tools from systems biology and bioinformatics into his work. Bioinformaticians and modellers are provided with a general perspective on microRNA biology in cancer, and the state-of-the-art in computational microRNA biology.
Learning And Inference In Computational Systems Biology
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Author : Neil D. Lawrence
language : en
Publisher:
Release Date : 2010
Learning And Inference In Computational Systems Biology written by Neil D. Lawrence and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
Tools and techniques for biological inference problems at scales ranging from genome-wide to pathway-specific. Computational systems biology unifies the mechanistic approach of systems biology with the data-driven approach of computational biology. Computational systems biology aims to develop algorithms that uncover the structure and parameterization of the underlying mechanistic model--in other words, to answer specific questions about the underlying mechanisms of a biological system--in a process that can be thought of as learning or inference. This volume offers state-of-the-art perspectives from computational biology, statistics, modeling, and machine learning on new methodologies for learning and inference in biological networks.The chapters offer practical approaches to biological inference problems ranging from genome-wide inference of genetic regulation to pathway-specific studies. Both deterministic models (based on ordinary differential equations) and stochastic models (which anticipate the increasing availability of data from small populations of cells) are considered. Several chapters emphasize Bayesian inference, so the editors have included an introduction to the philosophy of the Bayesian approach and an overview of current work on Bayesian inference. Taken together, the methods discussed by the experts in Learning and Inference in Computational Systems Biology provide a foundation upon which the next decade of research in systems biology can be built. Florence d'Alch e-Buc, John Angus, Matthew J. Beal, Nicholas Brunel, Ben Calderhead, Pei Gao, Mark Girolami, Andrew Golightly, Dirk Husmeier, Johannes Jaeger, Neil D. Lawrence, Juan Li, Kuang Lin, Pedro Mendes, Nicholas A. M. Monk, Eric Mjolsness, Manfred Opper, Claudia Rangel, Magnus Rattray, Andreas Ruttor, Guido Sanguinetti, Michalis Titsias, Vladislav Vyshemirsky, David L. Wild, Darren Wilkinson, Guy Yosiphon
Frontiers In Computational And Systems Biology
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Author : Jianfeng Feng
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-06-14
Frontiers In Computational And Systems Biology written by Jianfeng Feng and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-14 with Science categories.
Biological and biomedical studies have entered a new era over the past two decades thanks to the wide use of mathematical models and computational approaches. A booming of computational biology, which sheerly was a theoretician’s fantasy twenty years ago, has become a reality. Obsession with computational biology and theoretical approaches is evidenced in articles hailing the arrival of what are va- ously called quantitative biology, bioinformatics, theoretical biology, and systems biology. New technologies and data resources in genetics, such as the International HapMap project, enable large-scale studies, such as genome-wide association st- ies, which could potentially identify most common genetic variants as well as rare variants of the human DNA that may alter individual’s susceptibility to disease and the response to medical treatment. Meanwhile the multi-electrode recording from behaving animals makes it feasible to control the animal mental activity, which could potentially lead to the development of useful brain–machine interfaces. - bracing the sheer volume of genetic, genomic, and other type of data, an essential approach is, ?rst of all, to avoid drowning the true signal in the data. It has been witnessed that theoretical approach to biology has emerged as a powerful and st- ulating research paradigm in biological studies, which in turn leads to a new - search paradigm in mathematics, physics, and computer science and moves forward with the interplays among experimental studies and outcomes, simulation studies, and theoretical investigations.