Evolutionary Bioinformatics with a Scientific Computing Environment

Modern scientific research depends on computer technology to organize and analyze large data sets. This is more true for evolutionary bioinformatics—a relatively new discipline that has been developing rapidly as a sub-discipline of bioinformatics. Evolutionary bioinformatics devotes to leveraging the power of nature’s experiment of evolution to extract key findings from sequence and experimental data. Recent advances in highthroughput genotyping and sequencing technologies have changed the landscape of data collection. Acquisition of genomic data at the population scale has become increasingly costefficient. Genomic data sets are accumulating at an exponential rate and new types of genetic data are emerging. These come with the inherent challenges of new methods of statistical analysis and modeling. Indeed new technologies are producing data at a rate that outpaces our ability to analyze its biological meanings. Researchers are addressing this challenge by adopting mathematical and statistical software, computer modeling, and other computational and engineering methods. As a result, bioinformatics has become the latest engineering discipline. As computers provide the ability to process the complex models, high-performance computer languages have become a necessity for implementing state-of-the-art algorithms and methods. This chapter introduces one of such emerging programming languages—Matlab. Examples are provided to demonstrate Matlab-based solutions for preliminary and advanced analyses that are commonly used in molecular evolution and population genetics. The examples relating to molecular evolution focus on the mathematical modeling of sequence evolution; the examples relating to population genetics focus on summary statistics and neutrality tests. Several examples use functions in toolboxes specifically developed for molecular evolution and population genetics—MBEToolbox (Cai, Smith et al. 2005; Cai, Smith et al. 2006) and PGEToolbox (Cai 2008). The source code of some examples is simplified for the publication purpose.