Current Topics in Computational Molecular Biology
Computational molecular biology, or bioinformatics, draws on the disciplines of biology, mathematics, statistics, physics, chemistry, computer science, and engineering. It provides the computational support for functional genomics, which links the behavior of cells, organisms, and populations to the information encoded in the genomes, as well as for structural genomics. At the heart of all large-scale and high-throughput biotechnologies, it has a growing impact on health and medicine.
This survey of computational molecular biology covers traditional topics such as protein structure modeling and sequence alignment, and more recent ones such as expression data analysis and comparative genomics. It combines algorithmic, statistical, database, and AI-based methods for studying biological problems. The book also contains an introductory chapter, as well as one on general statistical modeling and computational techniques in molecular biology. Each chapter presents a self-contained review of a specific subject.
About the Editors
Tao Jiang is Professor of Computer Science and Engineering at the University of California, Riverside.
Ying Xu is a Senior Staff Scientist and Leader of the Computational Protein Structure Group at Oak Ridge National Laboratory.
Michael Q. Zhang is Associate Professor in Computational Biology and Bioinformatics at the Watson School of Biological Sciences, Cold Spring Harbor Laboratory.