Developing Bioinformatics Computer Skills

Chapter 12. Automating Data Analysis with Perl

As we've seen in previous chapters, a vast assortment of software tools exists for bioinformatics. Even though it's likely that someone has already written what you need, you will still encounter many situations in which the best solution is to do it yourself. In bioinformatics, that often means writing programs that sift through mountains of data to extract just the information you require. Perl, the Practical Extraction and Reporting Language, is ideally suited to this task.

Why Perl?

There are a lot of programming languages out there. In our survey of bioinformatics software, we have already seen programs written in Java, C, and FORTRAN. So, why use Perl? The answer is efficiency.^[*] Biological data is stored in enormous databases and text files. Sorting through and analyzing this data by hand (and it can be done) would take far too long, so the smart scientist writes computer tools to automate the process. Perl, with its highly developed capacity to detect patterns in data, and especially strings of text, is the most obvious choice. The next obvious choice would probably be Python. Python, the less well known of the two, is a fully object-oriented scripting language introduced by Guido van Rossum in 1988. Python has some outstanding contributed code, including a mature library for numerical methods, tools for building graphical user interfaces quickly and easily, and even a library of functions for structural biology. At the end ...