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Computational Systems Biology Approaches in Cancer Research.

Author: Inna Kuperstein; Emmanuel Barillot
Publisher: Boca Raton : CRC Press, 2019.
Series: Chapman & Hall/CRC Mathematical and Computational Biology
Edition/Format:   eBook : Document : English : First editionView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: (OCoLC)1101777114
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Inna Kuperstein; Emmanuel Barillot
ISBN: 9780429330179 0429330170 9781000682564 1000682560 9781000682748 1000682749 9781000682922 1000682927
OCLC Number: 1119391267
Description: 1 online resource (xviii, 167 pages).
Contents: Chapter 1. Pathway Databases and Network Resources in Cancer Chapter 2. Tumor Microenvironment Studies in Immuno-oncology Research Chapter 3.Multi-level Data Analysis: Tools and Approaches Chapter 4. Mathematical Modelling of Signalling Networks in Cancer Chapter 5. Single Cell Analysis in Cancer Chapter 6. Patient Stratification and Treatment Response Prediction
Series Title: Chapman & Hall/CRC Mathematical and Computational Biology

Abstract:

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'

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