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Fundamentals of Data Mining in Genomics and Proteomics

By doing so the book is following demands for a more statistical data mining approach to analyzing high-throughput data. Finally, by highlighting limitations and open issues Fundamentals of Data Mining in Genomics and Proteomics is intended to instigate critical thinking and avenues for new research...

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Bibliographic Details
Other Authors: Dubitzky, Werner (Editor), Granzow, Martin (Editor), Berrar, Daniel P. (Editor)
Format: eBook
Language:English
Published: New York, NY Springer US 2007, 2007
Edition:1st ed. 2007
Subjects:
Computer Appl. In Life Sciences
Statistics, General
Bioinformatics
Computational Biology 
Statistics 
Biochemistry, General
Bioinformatics 
Biotechnology
Proteomics
Biochemistry
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • to Genomic and Proteomic Data Analysis
  • Design Principles for Microarray Investigations
  • Pre-Processing DNA Microarray Data
  • Pre-Processing Mass Spectrometry Data
  • Visualization in Genomics and Proteomics
  • Clustering — Class Discovery in the Post-Genomic Era
  • Feature Selection and Dimensionality Reduction in Genomics and Proteomics
  • Resampling Strategies for Model Assessment and Selection
  • Classification of Genomic and Proteomic Data Using Support Vector Machines
  • Networks in Cell Biology
  • Identifying Important Explanatory Variables for Time-Varying Outcomes
  • Text Mining in Genomics and Proteomics

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