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Cancer Informatics in the Post Genomic Era

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Medical information science requires analytic tools. This is achieved by developing and assessing methods and systems for the acquisition, processing, and interpretation of patient data, aided by scientific discovery. Cancer Informatics in Post-Genomic Era provides both the necessary methodology and practical information tools.


Key challenges include integrating research and clinical care, sharing data, and establishing partnerships within and across sectors of patient diagnosis and treatment.


Addressing important clinical questions in cancer research will benefit from expanding computational biology.


The advent of genomic and proteomic technologies has ushered forth the era of genuine medicine. The promise of these advances is true "personalized medicine" where treatment strategies can be individually tailored and advance to initiating intervention before visible symptoms appear.

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Table of Contents
List of Figures ............................................................................................vii Foreword.................................................................................................... xi Preface .....................................................................................................xiii Contributing Authors ................................................................................. xv Acknowledgments.................................................................................... xxi Part I Introduction ................................................................................................. 1 Dennis A. Wigle and Igor Jurisica Part II Bio-Medical Platforms ............................................................................... 15 Ming Tsao In VivoSystems for Studying Cancer ....................................................... 25 Dennis A. Wigle, Jiang Liu, and Michael Johnston Molecular Subtypes of Cancer from Gene Expression Profiling ............... 45 Dennis A. Wigle and Igor Jurisica Mass Spectrometry-based Systems Biology ............................................ 59 Thomas Kislinger Part III Computational Platforms........................................................................... 85 Bill Wongand Igor Jurisica Informatics ................................................................................................ 87 Bill Wong Integrative Computational Biology .......................................................... 129 Igor Jurisica Part IV Future Steps and Challenges ................................................................. 147 Igor Jurisica and Dennis A. Wigle Glossary.................................................................................................. 151 References ............................................................................................. 159 Index ....................................................................................................... 179
http://www.springer.com/978-0-387-69320-0