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Biological data mining / edited by Jake Y. Chen, Stefano Lonardi. — Boca Raton ; London : CRC Press, 2010. – (58.17115/B615d) |
Contents
Contents
Preface
Editors
Contributors
Part I Sequence Structure, and Function
1 Consensus Structure Prediction for RNA Alignments
2 Invariant Geometric Properties of Secondary Structure Elements in Proteins
3 Discovering 3D Motifs in RNA
4 Protein Structure Classification Using Machine Learning Methods
5 Protein Surface Representation and Comparison: New Approaches in Structural Proteomics
6 Advanced Graph Mining Methods for Protein Analysis
7 Predicting Local Structure and Function of Proteins
Part II Genomics, Transcriptomics, and Proteomics
8 Computational Approaches for Genome Assembly Validation
9 Mining Patterns of Epistasis in Human Genetics
10 Discovery of Regulatory Mechanisms from Gene Expression Variation by eQTL Analysis
11 Statistical Approaches to Gene Expression Microarray Data Preprocessing
12 Application of Feature Selection and Classification to Computational Molecular Biology
13 Statistical Indices for Computational and Data Driven Class Discovery in Microarray Data
14 Computational Approaches to Peptide Retention Time Prediction for Proteomics
Part III Functional and Molecular Interaction Networks
15 Inferring Protein Functional Linkage Based on Sequence Information and Beyond
16 Computational Methods for Unraveling Transcriptional Regulatory Networks in Prokaryotes
17 Computational Methods for Analyzing and Modeling Biological Networks
18 Statistical Analysis of Biomolecular Networks
Part IV Literature, Ontology, and Knowledge Integration
19 Beyond Information Retrieval: Literature Mining for Biomedical Knowledge Discovery
20 Mining Biological Interactions from Biomedical Texts for Efficient Query Answering
21 Ontology-Based Knowledge Representation of Experiment Metadata in Biological Data Mining
22 Redescription Mining and Applications in Bioinformatics 561
Part V Genome Medicine Applications 587
23 Data Mining Tools and Techniques for Identification of Biomarkers for Cancer
24 Cancer Biomarker Prioritization: Assessing the in vivo Impact of in vitro Models by in silico Mining of Microarray Database, Literature, and Gene Annotation 615
25 Biomarker Discovery by Mining Glycomic and Lipidomic Data
26 Data Mining Chemical Structures and Biological Data
Index