Biological Data Mining | Jake Y. Chen, Stefano Lonardi | Taylor & Fran

Book

Biological Data Mining

ABSTRACT

Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplin

TABLE OF CONTENTS

part |2 pages

Part I Sequence, Structure, and Function

chapter 1|24 pages

Consensus Structure Prediction for RNA Alignments

chapter 2|22 pages

Invariant Geometric Properties of Secondary Structure Elements in Proteins

chapter 3|20 pages

Discovering 3D Motifs in RNA

chapter 4|20 pages

Protein Structure Classiﬁcation Using Machine Learning Methods

chapter 5|22 pages

Protein Surface Representation and Comparison: New Approaches in Structural Proteomics

chapter 6|26 pages

Advanced Graph Mining Methods for Protein Analysis

chapter 7|24 pages

Predicting Local Structure and Function of Proteins

part |2 pages

Part II: Genomics, Transcriptomics, and Proteomics

chapter 8|24 pages

Computational Approaches for Genome Assembly Validation

chapter 9|18 pages

Mining Patterns of Epistasis in Human Genetics

chapter 10|24 pages

Discovery of Regulatory Mechanisms from Gene Expression Variation by eQTL Analysis

chapter 11|28 pages

Statistical Approaches to Gene Expression Microarray Data Preprocessing

chapter 12|38 pages

Application of Feature Selection and Classiﬁcation to Computational Molecular Biology

chapter 13|42 pages

Statistical Indices for Computational and Data Driven Class Discovery in Microarray Data

chapter 14|14 pages

Computational Approaches to Peptide Retention Time Prediction for Proteomics

part |2 pages

Part III: Functional and Molecular Interaction Networks

chapter 15|24 pages

Inferring Protein Functional Linkage Based on Sequence Information and Beyond

chapter 16|20 pages

Computational Methods for Unraveling Transcriptional Regulatory Networks in Prokaryotes

chapter 17|32 pages

Computational Methods for Analyzing and Modeling Biological Networks Natasˇa Przˇulj and Tijana Milenkovic´

chapter 18|18 pages

Statistical Analysis of Biomolecular Networks

part |2 pages

Part IV: Literature, Ontology, and Knowledge Integration

chapter 19|36 pages

Beyond Information Retrieval: Literature Mining for Biomedical Knowledge Discovery

chapter 20|44 pages

Mining Biological Interactions from Biomedical Texts for Eﬃcient Query Answering

chapter 21|32 pages

Ontology-Based Knowledge Representation of Experiment Metadata in Biological Data Mining

chapter 22|26 pages

Redescription Mining and Applications in Bioinformatics

part |2 pages

Part V Genome Medicine Applications

chapter 23|26 pages

Data Mining Tools and Techniques for Identiﬁcation of Biomarkers for Cancer

chapter 24|12 pages

Cancer Biomarker Prioritization: Assessing the in vivo Impact of in vitro Models by in silico Mining of Microarray Database, Literature, and Gene Annotation

chapter 25|22 pages

Biomarker Discovery by Mining Glycomic and Lipidomic Data

chapter 26|40 pages

Data Mining Chemical Structures and Biological Data