Network-based Molecular Biology

This book provides a comprehensive coverage of problems and solutions for integrating high-throughput experimental data with structured biological knowledge. It includes details of classical and novel graph-theoretic and statistical/probabilistic approaches allowing not only an adequate study of complex molecular networks, but also the possibility to posit and test biologically meaningful hypotheses. The text offers a comprehensive coverage of topics related to integration of data with structured knowledge in depth sufficient for carrying out independent network-based research in computational/systems biology and bioinformatics.

The work is a suitable textbook for graduate students in bioinformatics, molecular biology, computational and systems biology, as well as a reference for researchers using network-based solutions for biological problems. The emphasis on network comparison and alignment and integration of high-throughput data with structured biological knowledge renders the book a timely addition to this rapidly growing research fields. This book can also be used as a supplementary text in applied mathematics with emphasis on graph theory, statistics, computer science, and machine learning.