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Bioinformatics Methods in Clinical Research

Overview of attention for book
Cover of 'Bioinformatics Methods in Clinical Research'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Omics
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    Chapter 2 Machine Learning: An Indispensable Tool in Bioinformatics
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    Chapter 3 SNP-PHAGE: High-Throughput SNP Discovery Pipeline
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    Chapter 4 R Classes and Methods for SNP Array Data
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    Chapter 5 Overview on Techniques in Cluster Analysis
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    Chapter 6 Nonalcoholic Steatohepatitis, Animal Models, and Biomarkers: What Is New?
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    Chapter 7 Biomarkers in Breast Cancer
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    Chapter 8 Genome-Wide Proximal Promoter Analysis and Interpretation
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    Chapter 9 Proteomics Facing the Combinatorial Problem
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    Chapter 10 Methods and Algorithms for Relative Quantitative Proteomics by Mass Spectrometry
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    Chapter 11 Feature Selection and Machine Learning with Mass Spectrometry Data
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    Chapter 12 Computational Methods for Analysis of Two-Dimensional Gels
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    Chapter 13 Mass Spectrometry in Epigenetic Research
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    Chapter 14 Computational Approaches to Metabolomics
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    Chapter 15 Algorithms and Methods for Correlating Experimental Results with Annotation Databases
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    Chapter 16 Analysis of biological processes and diseases using text mining approaches.
Attention for Chapter 9: Proteomics Facing the Combinatorial Problem
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