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Bioinformatics is the application of information technology to the management of biological data. Bioinformatics is first and foremost a biological science. It's often less about developing perfectly elegant algorithms than it is about answering practical questions. Bioinformaticians (or bioinformaticists, if you prefer) are the tool-builders, and it's critical that they understand biological problems as well as computational solutions in order to produce useful tools. Bioinformatics algorithms need to encompass complex scientific assumptions that can complicate programming and data modeling in unique ways. Research in bioinformatics and computational biology can encompass anything from the abstraction of the properties of a biological system into a mathematical or physical model, to the implementation of new algorithms for data analysis, to the development of databases and web tools to access them. This book introduces and explains many of the most popular tools used in bioinformatics research. the material in this book arranged to allow you to read it from start to finish or to skip around, digesting later sections before previous ones. It's divided into four parts: Part I: Chapter 1 defines bioinformatics as a discipline, delves into a bit of history, and provides a brief tour of what the book covers and why. Chapter 2 introduces the core concepts of bioinformatics and molecular biology and the technologies and research initiatives that have made increasing amounts of biological data available. It also covers the ever-growing list of basic computer procedures every biologist should know. Part II: Chapter 3 introduces Unix, then moves on to the basics of installing Linux on a PC and getting software up and running. Chapter 4 covers the ins and outs of moving around a Unix filesystem, including file hierarchies, naming schemes, commonly used directory commands, and working in a multiuser environment. Chapter 5 explains many Unix commands users will encounter on a daily basis, including commands for viewing, editing, and extracting information from files; regular expressions; shell scripts; and communicating with other computers. Part III: Chapter 6 is about the art of finding biological information on the Web. The chapter covers search engines and searching, where to find scientific articles and software, how to use the online information sources, and the public biological databases. Chapter 7 begins with a review of molecular evolution and then moves on to cover the basics of pairwise sequence-analysis techniques such as predicting gene location, global and local alignment, and local alignment-based searching against databases using BLAST and FASTA. The chapter concludes with coverage of multifunctional tools for sequence analysis. Chapter 8 moves on to study groups of related genes or proteins. It covers strategies for multiple sequence alignment with tools such as ClustalW and Jalview, then discusses tools for phylogenetic analysis, and constructing profiles and motifs. Chapter 9 covers 3D analysis of proteins and the tools used to compute their structural properties. The chapter begins with a review of protein chemistry and quickly moves to a discussion of web-based protein structure tools; structure classification, alignment, and analysis; solvent accessibility and solvent interactions; and computing physicochemical properties of proteins. The chapter concludes with structure optimization and a tour through protein resource databases. Chapter 10 covers the tools that determine the structures of proteins from their sequences. The chapter discusses feature detection in protein sequences, secondary structure prediction, predicting 3D structure. It concludes with an example project in protein modeling. Chapter 11 puts it all together. Up to now we've covered tools and techniques for analyzing single sequences or structures, and for comparing multiple sequences of single-gene length. This chapter discusses some of the datatypes and tools that are becoming available for studying the integrated function of all the genes in a genome, including sequencing an entire genome, accessing genome information on the Web, annotating and analyzing whole genome sequences, and emerging technologies and proteomics. Part IV: Chapter 12 shows you how a programming language such as Perl can help you sift through mountains of data to extract just the information you require. It won't teach you to program in Perl, but the chapter gives you a brief introduction to the language and includes examples to start you on your way toward learning to program. Chapter 13 is an introduction to database concepts. It covers the types of databases used in biological research, the database software that builds them, database languages (in particular, the SQL language), and developing web-based software that interacts with databases. Chapter 14 covers the computational tools and techniques that allow you to make sense of your results. The first part of the chapter introduces programs that are used to visualize data arising from bioinformatics research. They range from generalpurpose plotting and statistical packages for numerical data, such as Grace and gnuplot, to programs such as TEXshade that are dedicated to presenting sequence and structural information in an interpretable form. The second part of the chapter presents tools for data mining—the process of finding, interpreting, and evaluating patterns in large sets of data—in the context of applications in bioinformatics.