Computational Biology: Issues and Applications in Oncology (Applied Bioinformatics and Biostatistics in Cancer Research)

Computational Biology: Issues and Applications in Oncology provides a comprehensive report on recent techniques and results in computational oncology essential to the knowledge of scientists, engineers, as well as postgraduate students working on the areas of computational biology, bioinformatics, and medical informatics. With chapters timely prepared and written by experts in the field, this in-depth and up-to-date volume covers advanced statistical methods, heuristic algorithms, cluster analysis, data modeling, image and pattern analysis applied to cancer research. The literature and coverage of a spectrum of key topics in issues and applications in oncology make this a useful resource to computational life-science researchers wishing to enhance the most recent knowledge to facilitate their own investigations. Front Matter....Pages i-viii Identification of Relevant Genes from Microarray Experiments based on Partial Least Squares Weights: Application to Cancer Genomics....Pages 1-17 Geometric Biclustering and Its Applications to Cancer Tissue Classification Based on DNA Microarray Gene Expression Data....Pages 19-53 Statistical Analysis on Microarray Data: Selection of Gene Prognosis Signatures....Pages 55-76 Agent-Based Modeling of Ductal Carcinoma In Situ: Application to Patient-Specific Breast Cancer Modeling....Pages 77-111 Multicluster Class-Based Classification for the Diagnosis of Suspicious Areas in Digital Mammograms....Pages 113-123 Analysis of Cancer Data Using Evolutionary Computation....Pages 125-147 Analysis of Population-Based Genetic Association Studies Applied to Cancer Susceptibility and Prognosis....Pages 149-191 Selected Applications of Graph-Based Tracking Methods for Cancer Research....Pages 193-203 Recent Advances in Cell Classification for Cancer Research and Drug Discovery....Pages 205-226 Computational Tools and Resources for Systems Biology Approaches in Cancer....Pages 227-242 Laser Speckle Imaging for Blood Flow Analysis....Pages 243-271 The Challenges in Blood Proteomic Biomarker Discovery....Pages 273-299 Back Matter....Pages 301-309 Computational Biology: Issues And Applications In Oncology Provides A Comprehensive Report On Recent Techniques And Results In Computational Oncology Essential To The Knowledge Of Scientists, Engineers, As Well As Postgraduate Students Working On The Ares Of Computational Biology, Bioinformatics, And Medical Informatics.--back Cover. Tuan Pham, Editor. Includes Bibliographical References And Index. This book will introduce contributions, both methodological and technical, that have been made and are currently in progress in the field of computational biology as a resource in cancer research and oncology. This volume will illustrate the tools used in this area through a wide range of timely applications in genetics, genomics, and biomedical areas This volume covers techniques in computational biology and their applications in oncology. It details advanced statistical methods, heuristic algorithms, cluster analysis, data modeling, and image and pattern analysis applied to cancer research.