Parallel Computing for Bioinformatics and Computational Biology: Models, Enabling Technologies, and Case Studies

Albert Y. Zomaya, ed.

816 pages

US$125.00

Wiley-Interscience, 2006

ISBN: 0-471-71848-3

Bioinformatics and computational biology are up-and-coming disciplines that have recently made waves in technological fields and in the media. They're two of the few fields that require a wide spectrum of knowledge, from biology to computing and everything in between. Wikipedia (http://en.wikipedia.org/wiki/Bioinformatics) defines bioinformatics as involving "the use of techniques from applied mathematics, informatics, statistics, computer science, chemistry, and biochemistry to solve biological problems, usually on the molecular level."

Numerous papers and essays have been written on the subject, but finding the good ones is like looking for needles in a haystack. Parallel Computing for Bioinformatics and Computational Biology, a careful collection of 29 essays and papers, addresses this problem. Editor Albert Y. Zomaya has grouped the papers into five categories: algorithms, sequence analysis, phylogenetics, protein folding, and technology platforms.

Coming from a computing background with limited knowledge in biology, I didn't find the book a very difficult read. Understanding some basic biology concepts would have saved me some time spent referencing related materials on the Web. However, to appreciate the compiled text, you do need to understand parallel and supercomputing concepts.

The first section, on algorithms, starts by introducing computational biology, genes, genomes, and parallel computing concepts. Chapter one uses parallel Monte Carlo representation simulations to represent the HIV-1 virus. An entire chapter is dedicated to how stochasticity manifests in cellular processes and how to model, simulate, and visualize it. The section also presents an overview of current developments in simulating the diffusion and deformation of the human brain.

The next section covers some basics of molecular biology and supercomputers based on commercially available components. For example, it examines various versions of the Blast search tool for sequential databases and shows their results. The section further explores advanced methods for analyzing gene expression data that go beyond the standard techniques and distributed genetic algorithms used to sequence very large DNA molecules. This section also addresses how data mining techniques can provide more meaningful results from the data collected through simultaneous measurement of expression levels for thousands of genes.

Section three covers phylogenetics, the study of evolutionary relatedness among various groups of organisms. Phylogenetics is a routine task in biological research. This section analyzes different speed-up programs and examines their complexity.

Section four deals with different protein-folding and structure-prediction algorithms. It examines threading, or using information from known protein structures and various optimization opportunities.

The last section covers technology platforms. It introduces and defines Grid computing systems and explores the Cray supercomputer architecture. It also discusses and explores systems such as the Gamess (General Atomic and Molecular Electronic Structure System) quantum chemistry program, the ACDC (Advanced Computational Data Center) and Grid2003 grids, various FPGAs (field programmable gate arrays), and grid middleware.

This book is the only one I know of that offers a collection of bioinformatics papers. Biotechnology is a fairly young discipline. Many of the solutions this book discusses aren't mainstream or widely used, and many are still in the development stages. I expect we'll see the solutions evolve over the next few years. This text is more of a building block on computational biology concepts to help researchers and students work on more innovative ideas. Overall, I would give this collection an 8 on a scale of 10.

The views and opinions expressed in this article are the author's and do not necessarily represent the views of Microsoft Corporation.

Milan Lathia is a program manager with Microsoft Corporation. Contact him at milanl@microsoft.com.