Unix

Learning Red Hat Linux and Learning Debian GNU Linux. B. McCarty. O'Reilly & Associates. Good introductory guides to setting up systems with these releases of Linux.

Learning the Unix Operating System. J. Peek, G. Todino, and J. Strang. O'Reilly & Associates. A concise introduction to Unix for the beginner.

The Linux Desk Reference. S. Hawkins and J. Brockmeier. Prentice Hall.

Linux in a Nutshell. Siever, et al. O'Reilly & Associates. A no-nonsense quick-reference guide to Linux commands.

Running Linux. M. Welsh and L. Kaufman. O'Reilly & Associates. A relatively comprehensive how-to guide for setting up a Linux system.

Unix for the Impatient. P. Abrahams and B. Larson. Addison Wesley. A detailed yet user-friendly presentation of everything a Unix user needs to know. (My first and still favorite Unix guide. CJG)

Unix in a Nutshell. A. Robbins. O'Reilly & Associates. A no-nonsense quick-reference guide to Unix commands.

SysAdmin

Essential System Administration. A. Frisch. O'Reilly & Associates. A detailed guide to administration of Unix systems.

Using csh & tcsh. P. DuBois. O'Reilly & Associates. A detailed guide to using two of the most common shell environments.

Perl

Elements of Programming in Perl. A. L. Johnson. Manning Publications. Good introduction to Perl as a first programming language

Learning Perl. R. Schwartz and T. Christiansen. O'Reilly & Associates. Introduction to Perl but assumes prior experience with another programming language.

For a more detailed, biology-oriented Perl tutorial, we recommend the one available online at Lincoln Stein's laboratory page at Cold Spring Harbor Labs, http://stein.cshl.org.

Mastering Algorithms in Perl. J. Orwant, J. Hietaniemi, and J. Macdonald. O'Reilly & Associates. Both this book and the next cover interesting things that can be done with Perl.

Perl Cookbook. T. Christiansen and N. Torkington. O'Reilly & Associates.

Programming Perl. L. Wall, T. Christiansen, and J. Orwant. O'Reilly & Associates. The bible of Perl.

General Reference

Finding Out About: Search Engine Technology from a Cognitive Perspective. R. Belew. Cambridge University Press. A fascinating discussion of information retrieval and the process of web-based research from a cognitive science perspective. Both practical and philosophical aspects are covered.

All three of the following books cover general programming techniques:

Code Complete. S. McConnell. Microsoft Press.

The Practice of Programming. B. W. Kernighan and R. Pike. Addison Wesley

Programming Pearls. J. Bentley. Addison Wesley

Bioinformatics Reference

Bioinformatics: A Machine Learning Approach. P. Baldi and S. Brunak. MIT Press. The authors have firsthand experience with applying neural networks and hidden Markov models to sequence analysis, including genefinding, DNA feature detection, and protein family modeling.

Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins. A. D. Baxevanis and B. F. F. Ouellette. John Wiley & Sons. A gentle introduction to biological information and bioinformatics tools on the Web, focused on NCBI tools.

Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. R. Durbin, S. Eddy, A. Krogh, and G. Mitchison. Cambridge University Press. A rigorous presentation of the statistical and algorithmic basis of sequence analysis methods, including pairwise and multiple sequence analysis, motif discovery, and phylogenetic analysis.

Molecular Systematics. D. M. Hillis, C. Moritz, and B. K. Mable, Eds. Sinauer and Associates. Although the first two-thirds of the book are devoted to experimental methods, the chapters on the methods for inferring and applying phylogenies provide a rigorous and comprehensive follow-up to the Graur and Li book.

Molecular Biology/Biology Reference

Fundamentals of Molecular Evolution. D. Graur, W-H. Li. Sinauer and Associates. A readable explanation of the mechanisms by which genomes change over time, with a discussion of phylogenetic inference based on molecular data.

Molecular Systematics. D. M. Hillis, C. Moritz, and B. K. Mable, eds. Sinauer and Associates. Although the first two-thirds of the book are devoted to experimental methods, the chapters on the methods for inferring and applying phylogenies provide a rigorous and comprehensive follow-up to the Graur and Li book.

Protein Structure and Biophysics

Intermolecular and Surface Forces. J. Israelachvili. Academic Press. A must-have book for any serious student of macromolecular structure and molecular biophysics. This book details the physical chemistry of interactions among molecules and between molecules and surfaces.

Introduction to Protein Structure. C-I. Branden and J. Tooze. Garland Publishing. An illustrated guide to the basic principles of protein structure and modeling.

Genomics

Genomes. T. A. Brown. Wiley-Liss. A thorough presentation of molecular genetics from the genomics perspective.

Genomics: The Science and Technology Behind the Human Genome Project. C. R. Cantor and C. L. Smith. John Wiley & Sons. If you want to understand, in detail, how genomic sequence data is obtained, this is the book to have. It exhaustively details experimental protocols for sequencing and mapping and explores the future of sequencing technology.

Biotechnology

DNA Microarrays: A Practical Approach. M. Schena, ed. Oxford University Press. An introduction to the basics of DNA microarray technology and its applications.

Proteome Research: New Frontiers in Functional Genomics. M. R. Wilkins, K. L. Williams, R. D. Appel, and D. F. Hochstrasser, eds. Springer. An introduction to new techniques for protein identification and analysis, from 2D-PAGE to MALDI-TOF and beyond.

Databases

CGI Programming with Perl. S. Guelich, S. Gundavaram, and G. Birznieks. O'Reilly & Associates. An introduction to the CGI protocol for generating active-content web pages. If you are interested in web software development, this book is an essential starting point.

Joe Celko's Data and Databases: Concepts in Practice. J. Celko. Morgan Kaufman. A good introduction to relational database concepts and the use of SQL.

MySQL. P. DuBois. New Riders. A detailed guide to using MySQL. Detailed coverage of administration and security issues.

MySQL & mSQL. R. J. Yarger, G. Reese, and T. King. O'Reilly & Associates. An introduction to using MySQL and mSQL; also contains an introduction to RDB concepts and database normalization. O'Reilly also publishes a collection of reference books about Oracle, if you prefer to start using Oracle from the beginning.

Visualization

Understanding Robust and Exploratory Data Analysis. D. C. Hoaglin, et al. eds. John Wiley & Sons. A classic book on visualization techniques. Don't be put off by the fact that the focus of the book is on techniques for doing analysis by hand rather than the latest computational tricks: the methods described are implemented in many visualization packages and are easily applicable to the latest bioinformatics problems.

The Visual Display of Quantitative Information, Envisioning Information, and Visual Explanations. E Tufte. Graphics Press. In each book, Tufte illustrates good and bad practices in visual data analysis using examples from newspapers, advertising campaigns, and train schedules (to name a few).

The Visualization Toolkit: An Object-Oriented Approach to 3-D Graphics. W. Schroeder, K. Martin, and B. Lorensen. Prentice Hall Computer Books. For those readers who want a more active role in designing visualization tools, this book combines introductions to computer graphics and visualization practices with a description of a working implementation of a complete visualization system, the Visualization Toolkit (VTK). VTK is an object-oriented, scriptable framework for building visualization tools. It is available from http://www.kitware.com.

Data Mining

Data Mining: Practical Machine Learning. I. Witten and E. Frank. Morgan Kaufman. A clearly written introduction to data mining methods. It comes with documentation for the authors' WEKA program suite, a set of data mining tools written in Java that can be freely downloaded from their web site.

Data Preparation for Data Mining. D. Pyle. Morgan Kaufman. For readers looking for more insight into the data-preparation process.

Machine Learning. T. Mitchell. McGraw-Hill. Provides a complementary treatment of the same methods as the previous book and is more formal but no less practical.

Modern Applied Statistics with S-Plus. Brian D. Ripley and William N. Venables. Springer Verlag.

Numerical Recipes in C. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery. Cambridge University Press. A comprehensive introduction to the techniques that underlie all nontrivial methods for data analysis. Combines mathematical explanations with efficient C implementations. In addition to the hardcopy form, the entire book and all its source code are available online at no charge from http://www.nr.com.