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Biomedical Sciences - Cancer Research | Computational Biology - Issues and Applications in Oncology

Computational Biology

Issues and Applications in Oncology

Pham, Tuan (Ed.)

2010, VIII, 309p. 90 illus., 26 illus. in color.

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  • Covers the entire spectrum of techniques in computational biology and their applications in the field of oncology, including microarrays, gels, mass spectra, SNPs and haplotypes
  • Includes brief discussion of the applications of systems biology

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.

Content Level » Professional/practitioner

Keywords » Radiologieinformationssystem - carcinoma - classification - cluster analysis - diagnosis - imaging

Related subjects » Cancer Research - Pharmacology & Toxicology

Table of contents 

Computational Biology: Issues and Applications in Oncology Editor: Tuan D. Pham List of Chapters Chapter 1 Identification of relevant genes from microarray experiments based on partial least squares weights: Application to cancer genomics Ying Chen, Danh V. Nguyen Chapter 2 Geometric biclustering and its applications to cancer tissue classification based on DNA microarray gene expression data Hongya Zhao, Hong Yan Chapter 3 Statistical analysis on microarray data: selection of gene prognosis signatures Kim-Anh Lê Cao, Geoffrey J. McLachlan Chapter 4 Agent-based modeling of ductal carcinoma in situ: application to patient-specific breast cancer modeling Paul Macklin, Jahun Kim, Giovanna Tomaiuolo, Mary E. Edgerton, Vittorio Cristini Chapter 5 Multi-cluster class based classification for the diagnosis of suspicious areas in digital mammograms Brijesh Verma Chapter 6 Analysis of cancer data using evolutionary computation Cuong C. To, Tuan D. Pham Chapter 7 Analysis of population-based genetic association studies applied to cancer susceptibility and prognosis Xavier Solé, Juan Ramón González, Víctor Moreno Chapter 8 Selected applications of graph-based tracking methods for cancer research Pascal Vallotton, Lilian Soon Chapter 9 Recent advances in cell classification for cancer research and drug discovery Dat T. Tran, Tuan D. Pham Chapter 10 Computational tools and resources for systems biology approaches in cancer Andriani Daskalaki, Christoph Wierling, Ralf Herwig Chapter 11 Laser speckle imaging for blood flow analyses Thinh M. Le, J.S. Paul,H. Al-Nashash, A. Tan, A.R. Luft, F-S. Sheu, S.H. Ong Chapter 12 The Challenges in Blood Proteomic Biomarker Discovery Guangxu Jin, Xiaobo Zhou, Honghui Wang, Stephen T.C. Wong

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