Includes cutting-edge methods and protocols

Provides step-by-step detail essential for reproducible results

Contains key notes and implementation advice from the experts

3D Computational Modeling of Proteins Using Sparse Paramagnetic NMR Data.- Inferring Function from Homology.- Inferring Functional Relationships from Conservation of Gene Order.- Structural and Functional Annotation of Long Non-Coding RNAs.- Construction of Functional Gene Networks Using Phylogenetic Profiles.- Inferring Genome-Wide Interaction Networks.- Integrating Heterogeneous Datasets for Cancer Module Identification.- Metabolic Pathway Mining.- Analysis of Genome-Wide Association Data.- Adjusting for Familial Relatedness in the Analysis of GWAS Data.- Analysis of Quantitative Trait Loci.- High-Dimensional Profiling for Computational Diagnosis.- Molecular Similarity Concepts for Informatics Applications.- Compound Data Mining for Drug Discovery.- Studying Antibody Repertoires with Next-Generation Sequencing.- Using the QAPgrid Visualization Approach for Biomarker Identification of Cell-Specific Transcriptomic Signatures.- Computer-Aided Breast Cancer Diagnosis with Optimal Feature Sets: Reduction Rules and Optimization Techniques.- Inference Method for Developing Mathematical Models of Cell Signaling Pathways Using Proteomic Datasets.- Clustering.- Parameterized Algorithmics for Finding Exact Solutions of NP-Hard Biological Problems.- Information Visualization for Biological Data.