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Bioinformatics Computing is a practical guide to computing in the burgeoning field of bioinformatics—the study of how information is represented and transmitted in biological systems, starting at the molecular level. This book, which is intended for molecular biologists at all levels of training and practice, assumes the reader is computer literate with modest computer skills, but has little or no formal computer science training.In bioinformatics, as in many new fields, researchers and entrepreneurs at the fringes—where technologies from different fields interact—are making the greatest strides.Proponents of biotechnology contend that we are on the verge of controlling the coding of living things, and concomitant breakthroughs in biomedical engineering, therapeutics, and drug development. This book is organized into modular, stand-alone topics related to bioinformatics computing according to the following chapters: Chapter 1: THE CENTRAL DOGMA - This chapter provides an overview of bioinformatics, using the Central Dogma as the organizing theme. It explores the relationship of molecular biology and bioinformatics to computer science, and how the purview of computational bioinformatics necessarily extends from the molecular to the clinical medicine level. Chapter 2: DATABASES - Bioinformatics is characterized by an abundance of data stored in very large databases. The practical computer technologies related to very large databases are discussed, with an emphasis on object-oriented database methods, given that traditional relational database technology may be ill-suited for some bioinformatics needs. Data warehousing, data dictionaries, database design, and knowledge management techniques related to bioinformatics are also discussed in detail. Chapter 3: NETWORKS - This chapter explores the information technology infrastructure of bioinformatics, including the Internet, World Wide Web, intranets, wireless systems, and other network technologies that apply directly to sharing, manipulating, and archiving sequence data and other bioinformatics information. This chapter reviews Web-based resources for researchers, such as GenBank and other systems maintained by NCBI, NIH, and other government agencies. The Great Global Grid and its potential for transforming the field of bioinformatics is also discussed. Chapter 4: SEARCH ENGINES - The exponentially increasing amounts of data accessible in digital form over the Internet, from gene sequences to published references to the experimental methods used to determine specific sequences, is only accessible through advanced search engine technologies. This chapter details search engine operations related to the major online bioinformatics resources. Chapter 5: DATA VISUALIZATION - Exploring the possible configurations of folded proteins has proven to be virtually impossible by simply studying linear sequences of bases. However, sophisticated 3D visualization techniques allow researchers to use their visual and spatial reasoning abilities to understand the probable workings of proteins and other structures. This chapter explores data visualization techniques that apply to bioinformatics, from methods of generating 2D and 3D renderings of protein structures to graphing the results of the statistical analysis of protein structures. Chapter 6: STATISTICS - The randomness inherent in any sampling process— such as measuring the mRNA levels of thousands of genes simultaneously with microarray techniques, or assessing the similarity between protein sequences—necessarily involves probability and statistical methods. This chapter provides an in-depth discussion of the statistical techniques applicable to molecular biology, addressing topics such as statistical analysis of structural features, gene prediction, how to extract maximal value from small sample sets, and quantifying uncertainty in sequencing results. Chapter 7: DATA MINING - Given an ever-increasing store of sequence and protein data from several ongoing genome projects, data mining the sequences has become a field of research in its own right. Many bioinformatics scientists conduct important research from their PCs, without ever entering a wet lab or seeing a sequencing machine. The aim of this chapter is to explore data-mining techniques, using technologies, such as the Perl language, that are uniquely suited to searching through data strings. Other issues covered include taxonomies, profiling sequences, and the variety of tools available to researchers involved in mining the data in GenBank and other very large bioinformatics databases. Chapter 8: PATTERN MATCHING - Expert systems and classical pattern matching or AI techniques—from reasoning under uncertainty and machine learning to image and pattern recognition—have direct, practical applicability to molecular biology research. This chapter covers a variety of pattern-matching approaches, using molecular biology as a working context. For example, microarray research lends itself to machine learning, in that it is humanly impossible to follow thousands of parallel reactions unaided, and several gene-prediction applications are based on neural network pattern-matching engines. The strengths and weakness of various pattern-matching approaches in bioinformatics are discussed. Chapter 9: MODELING AND SIMULATION - This chapter covers a variety of simulation techniques, in the context of computer modeling events from drug-protein interactions and probable protein folding configurations to the analysis of potential biological pathways. The application of event-driven, time-driven, and hybrid simulation techniques are discussed, as well as linking computer simulations with visualization techniques. Chapter 10: COLLABORATION - Bioinformatics is characterized by a high degree of cooperation among the researchers who contribute their part to the whole knowledge base of genomics and proteomics. As such, this chapter explores the details of collaboration with enabling technologies that facilitate multimedia communications, real-time videoconferencing, and Web-based application sharing of molecular biology information and knowledge.