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The pharmaceutical industry relies on numerous well-designed experiments involving high-throughput techniques and in silico approaches to analyze potential drug targets. These in silico methods are often predictive, yielding faster and less expensive analyses than traditional in vivo or in vitro procedures. In Silico Technologies in Drug Target Identification and Validation addresses the challenge of testing a growing number of new potential targets and reviews currently available in silico approaches for identifying and validating these targets. The book emphasizes computational tools, public and commercial databases, mathematical methods, and software for interpreting complex experimental data. The book describes how these tools are used to visualize a target structure, identify binding sites, and predict behavior. World-renowned researchers cover many topics not typically found in most informatics books, including functional annotation, siRNA design, pathways, text mining, ontologies, systems biology, database management, data pipelining, and pharmacogenomics. Covering issues that range from prescreening target selection to genetic modeling and valuable data integration, In Silico Technologies in Drug Target Identification and Validation is a self-contained and practical guide to the various computational tools that can accelerate the identification and validation stages of drug target discovery and determine the biological functionality of potential targets more effectively. Daniel E. Levy, editor of the Drug Discovery Series, is the founder of DEL BioPharma, a consulting service for drug discovery programs. He also maintains a blog that explores organic chemistry.
Sequence Analysis in a Nutshell: A Guide to Common Tools and Databases pulls together all of the vital information about the most commonly used databases, analytical tools, and tables used in sequence analysis. The book contains details and examples of the common database formats (GenBank, EMBL, SWISS-PROT) and the GenBank/EMBL/DDBJ Feature Table Definitions. It also provides the command line syntax for popular analysis applications such as Readseq and MEME/MAST, BLAST, ClustalW, and the EMBOSS suite, as well as tables of nucleotide, genetic, and amino acid codes. Written in O'Reilly's enormously popular, straightforward "Nutshell" format, this book draws together essential information for bioinformaticians in industry and academia, as well as for students. If sequence analysis is part of your daily life, you'll want this easy-to-use book on your desk.
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