Beginning Perl for Bioinformatics
by James Tisdall
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Book Summary Information
Author: James TisdallEdition: Paperback
Audio: English (Original Language); French (Unknown); English (Published)
Format: Illustrated
Published: 2001-10-15
ISBN: 0596000804
Number of pages: 400
Publisher: O'Reilly Media, Inc.
Book Reviews of Beginning Perl for Bioinformatics
Book Review: A practical introduction to programming for biologists
Summary: 5 Stars
Although this book was written for biologists with no previous programming experience who have decided they need to learn to program in PERL, it is also useful for programmers entering the field of bioinformatics who need to learn the language. However, you should have some background in biology or else you'll be lost as to the purpose of the examples. That's because almost all of the examples and exercises are based on real biological problems, and this book will give you a good introduction to the most common bioinformatics programming problems and the most common computer-based biological data. This book is over five years old, but it still stands alone in that what it does it does better than any other book I've run across. The follow-on to this book is "Mastering Perl for Bioinformatics", and I recommend that book for both CS and biologist types that want to get into the more advanced parts of PERL and yet stay in the realm of learning the language via real biological problems. The following is a short run down of each chapter:
1. Biology and Computer Science - Covers some key concepts in molecular biology, as well as how biology and computer science fit together.
2. Getting Started with Perl - Shows you how to get Perl running on your computer and also talks about Perl's benefits.
3. The Art of Programming - Provides an overview as to how programmers accomplish their jobs. Some of the most important practical strategies good programmers use are explained, and where to find answers to questions that arise while you are programming is carefully laid out. These ideas are made concrete by brief narrative case studies that show how programmers, given a problem, find its solution.
4. Sequences and Strings - You start writing Perl programs with DNA and proteins. The programs transcribe DNA to RNA, concatenate sequences, make the reverse complement of DNA, and read sequence data from files. This is the first chapter to conclude with exercises.
5. Motifs and Loops - Continues demonstrating the basics of the Perl language with programs that search for motifs in DNA or protein, interact with users at the keyboard, write data to files, use loops and conditional tests, use regular expressions, and operate on strings and arrays.
6. Subroutines and Bugs -Extends the basic knowledge of Perl in two main directions: subroutines, which are an important way to structure programs, and the use of the Perl debugger, which can examine in detail a running Perl program.
7. Mutations and Randomizations - Genetic mutations, fundamental to biology, are modelled as random events using the random number generator in Perl. This chapter uses random numbers to generate DNA sequence data sets, and to repeatedly mutate DNA sequence. Loops, subroutines, and lexical scoping are also discussed.
8. The Genetic Code - How to translate DNA to proteins, using the genetic code. It also covers a good bit more of the Perl programming language, such as the hash data type, sorted and unsorted arrays, binary search, relational databases, and DBM, and how to handle FASTA formatted sequence data.
9. Restriction Maps and Regular Expressions - An introduction to Perl regular expressions. The main focus of the chapter is the development of a program to calculate a restriction map for a DNA sequence.
10. GenBank - The Genetic Sequence Data Bank (GenBank) is central to modern biology and bioinformatics. In this chapter, you learn how to write programs to extract information from GenBank files and libraries. You will also make a database to create your own rapid access lookups on a GenBank library.
11. Protein Data Bank - Develops a program that can parse Protein Data Bank (PDB) files. Some interesting Perl techniques are encountered while doing so, such as finding and iterating over lots of files and controlling other bioinformatics programs from a Perl program.
12. BLAST - Develops some code to parse a BLAST output file. Also mentioned are the Bioperl project and its BLAST parser, and some additional ways to format output in Perl.
13. Further Topics - Looks at topics beyond the scope of this book. These topics include sequence alignment methods like the Smith-Waterman algorithm and microarray techniques that enable the measurement of the relative levels of thousands of gene transcripts at a time. These topics are only briefly mentioned, and you are shown places outside of the book to get further information.
Appendix A - Resources for Perl and for bioinformatics programming, such as books and Internet sites.
Appendix B - Summary of those parts of the Perl language that will be most useful as you read this book.
Summary of Beginning Perl for Bioinformatics
With its highly developed capacity to detect patterns in data, Perl has become one of the most popular languages for biological data analysis. But if you're a biologist with little or no programming experience, starting out in Perl can be a challenge. Many biologists have a difficult time learning how to apply the language to bioinformatics. The most popular Perl programming books are often too theoretical and too focused on computer science for a non-programming biologist who needs to solve very specific problems."Beginning Perl for Bioinformatics" is designed to get you quickly over the Perl language barrier by approaching programming as an important new laboratory skill, revealing Perl programs and techniques that are immediately useful in the lab. Each chapter focuses on solving a particular bioinformatics problem or class of problems, starting with the simplest and increasing in complexity as the book progresses. Each chapter includes programming exercises and teaches bioinformatics by showing and modifying programs that deal with various kinds of practical biological problems. By the end of the book you'll have a solid understanding of Perl basics, a collection of programs for such tasks as parsing BLAST and GenBank, and the skills to take on more advanced bioinformatics programming. Some of the later chapters focus in greater detail on specific bioinformatics topics. This book is suitable for use as a classroom textbook, for self-study, and as a reference.
The book covers:
Programming basics and working with DNA sequences and strings
Debugging your code
Simulating gene mutations using random number generators
Regular expressions and finding motifs indata
Arrays, hashes, and relational databases
Regular expressions and restriction maps
Using Perl to parse PDB records, annotations in GenBank, and BLAST output
Biology, it seems, is a good showcase for the talents of Perl. Newcomers to Perl who understand biological information will find James Tisdall's Beginning Perl for Bioinformatics to be an excellent compendium of examples. Teachers of Perl will likewise find the text to be filled with fresh programming illustrations of growing scientific importance. Seasoned Perlmongers who want to learn biology, however, should search elsewhere, as Tisdall's emphasis is on Perl's logic rather than Mother Nature's.
Departing from O'Reilly's earlier monograph Developing Bioinformatic Computer Skills, Tisdall's text is organized aggressively along didactic lines. Nearly all of the 13 chapters begin with twin bullet lists of Perl programming tools and the bioinformatic methods that require them. Likewise, the chapters end with exercises. String concatenation is illustrated with gene splicing, and regular expressions are taught with gene transcription and motif searching.
Tisdall emphasizes sequence examples throughout, leading up to an introduction to a Perl interface for the NIH GenBank biological database and the widely used BLAST sequence alignment tool. After a brief discussion of three-dimensional protein structure, he returns to sequence extraction and secondary structure prediction.
Tisdall's goal is to boost the beginning programmer into a domain of self-learning. He imparts essential etiquette for the success of programming newbies: use the wealth or resources available, from user documentation to Web site surveys to FAQs to How-To's to news groups and finally to direct personal appeals for help from a senior colleague. A well-plugged-in bioinformatics Perl student will soon discover Bioperl, an open-source effort to bring research-grade bioinformatic tools to the Perl community. Bioperl is described briefly at the end of Tisdall's book and will reportedly be a forthcoming title of its own in the O'Reilly bioinformatics series.
Although he introduces bioinformatics as an academic discipline, Tisdall treats it as a trade throughout his book. He indicates that open questions and computational hard problems exist, but does not describe what they are or how they are being tackled. Ultimately, Tisdall presents bioinformatics as another arrow in a bench scientist's quiver, very much like HPLC, 2D-PAGE, and the various spectroscopies.
As odd as a "bioinformatics-as-tool" book may be to its research proponents, the reduction of bioinformatics to trade status both deflates and vindicates the years of research, as Tisdall's work attests. --Peter Leopold
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