Bioinformatics in Cancer and Cancer Therapy / Edition 1by Gavin J. Gordon
Pub. Date: 10/22/2014
Publisher: Springer-Verlag New York, LLC
Bioinformatics can be loosely defined as the collection, classification, storage, and analysis of biochemical and biological information using computers and mathematical algorithms. Although no single person or group started the field wholly on their own, Temple Smith, Ph.D., a professor at Boston University, is generally credited with coining the/strong>
Bioinformatics can be loosely defined as the collection, classification, storage, and analysis of biochemical and biological information using computers and mathematical algorithms. Although no single person or group started the field wholly on their own, Temple Smith, Ph.D., a professor at Boston University, is generally credited with coining the term. Bioinformatics represents a marriage of biology, medicine, computer science, physics, and mathematics, fields of study that have historically existed as mutually exclusive disciplines.
Concurrently, bioinformatics has vaulted into the public’s eye in lay newspapers and magazines, most notably in the area of (personalized) DNA sequencing. The combined result is that bioinformatics is being heralded as a panacea to the current limitations in the clinical management of cancer. While certainly over optimistic in some regards, this designation is not without promise particularly in the area of cancer diagnosis and prognosis.
The focus of this book is to: i) to provide a historical and technical perspective on the analytical techniques, methodologies, and platforms used in bioinformatics experiments, ii) to show how a bioinformatics approach has been used to characterize various cancer-related processes, and iii) to demonstrate how a bioinformatics approach is being used to bridge basic science and the clinical arena to positively impact patient care and management.
Table of ContentsTable of Contents for Bioinformatics in Cancer and Cancer Therapy Preface Chapter 1: The Emergence of Bioinformatics: Historical Perspective, Quick Overview and Future Trends Christos A. Ouzounis Chapter 2: The Statistical Design and Interpretation of Microarray Experiments Kevin K. Dobbin and Richard M. Simon Chapter 3: Whole Genome Analysis of Cancer Steven A. Enkemann, James M. McLoughlin, Eric H. Jensen, and Timothy J. Yeatman
Chapter 4: Bioinformatics Approaches to the Analysis of the Transcriptome of Animal Models of Cancer Mark J. Hoenerhoff, Aleksandra A. Michalowska, Ting-Hu Qiu, and Jeffery E. Green Chapter 5: Significance of Aberrant Expression of MicroRNAs in Cancer Cells George A. Calin, Chang-gong Liu, Manuela Ferracin, Stefano Volinia, Massimo Negrini, and Carlo M. Croce Chapter 6: Proteomic Methods in Cancer Research Scot Weinberger and Egisto Boschetti Chapter 7: Comprehensive Genomic Profiling for Biomarker Discovery for Cancer Detection, Diagnostics and Prognostics Xiaofeng Zhou, Nagesh P. Rao, Steven W. Cole, and David T. Wong Chapter 8: Gene Expression Profiling of the Leukemias: Oncogenesis, Drug Responsiveness, and Prediction of Clinical Outcome Lars Bullinger, Hartmut Dohner, and Jonathan R. Pollack Chapter 9: Personalized Medicine in the Clinical Management of Colorectal Cancer Anthony El-Khoueiry and Heinz Josef Lenz Chapter 10: PIK3CA Gene Alterations in Human Cancers Sérgia Velho, Carla Oliveira, and Raquel Seruca
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