Gene sequence data is the most abundant type of data available, and if you're interested in analyzing it, you'll find a wealth of computational methods and tools to help you. In fact, finding the data is not the challenge at all; rather it is dealing with the plethora of flat file formats used to process the sequence entries and trying to remember what their specific field codes mean. If you survive by surrounding yourself with well-thumbed hard copies of readme files or remembering exactly where to look for the details when you need them, then Sequence Analysis in a Nutshell: A Guide to Common Tools and Databases is for you. This book is a handy resource, as well as an invaluable reference, for anyone who needs to know about the practical aspects and mechanics of sequence analysis. 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 is partitioned into three fundamental areas to help you maximize your use of the content. The first section, "Databases" contains examples of flatfiles from key databases (GenBank, EMBL, SWISS-PROT), the definitions of the codes or fields used in each database, and the sequence feature types/terms and qualifiers for the nucleotide and protein databases. The second section, "Tools" provides the command line syntax for popular applications such as ReadSeq, MEME/MAST, BLAST, ClustalW, and the EMBOSS suite of analytical tools. The third section, "Appendixes" concentrates on information essential to understanding the individual components that make up a biological sequence. The tables in this section include nucleotide and protein codes, genetic codes, as well as other relevant information. 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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Scott Markel is a Principal Software Architect at LION bioscience Inc., where he is responsible for providing architectural direction in the development of software for the life sciences, including the use and development of standards. He is a co-chair of the Life Sciences Research Domain Task Force of the Object Management Group, and also chairs the LSR's Architecture and Roadmap Working Group. Prior to working at LION, Scott worked at NetGenics, Johnson & Johnson Pharmaceutical Research & Development, and Sarnoff Corporation. He has a Ph.D. in mathematics from the University of Wisconsin-Madison. When Scott's not working or writing he enjoys spending time with his wife and kids, reading European history books, and just enjoying life in sunny San Diego.
Darryl LeÃ3n is a Principal Scientific Architect at LION bioscience Inc., where he is responsible for providing scientific direction in the development of software for the life sciences. Prior to working at LION, Darryl worked at NetGenics, DoubleTwist, and Genset. He has taught at California Polytechnic State University, San Luis Obispo, and currently teaches a bioinformatics class at U.C. Santa Cruz Extension and U.C. San Diego Extension. He is also a member of the Bioinformatics Advisory Committee at U.C. San Diego Extension. Darryl has a Ph. D. in biochemistry from the University of California, San Diego and did his postdoctoral research at the University of California, Santa Cruz.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : New. Gene sequence data is the most abundant type of data available, and if you're interested in analyzing it, you'll find a wealth of computational methods and tools to help you. In fact, finding the data is not the challenge at all; rather it is dealing with the plethora of flat file formats used to process the sequence entries and trying to remember what their specific field codes mean. If you survive by surrounding yourself with well-thumbed hard copies of readme files or remembering exactly where to look for the details when you need them, then Sequence Analysis in a Nutshell: A Guide to Common Tools and Databases is for you. This book is a handy resource, as well as an invaluable reference, for anyone who needs to know about the practical aspects and mechanics of sequence analysis. 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 is partitioned into three fundamental areas to help you maximize your use of the content.The first section, "Databases" contains examples of flatfiles from key databases (GenBank, EMBL, SWISS-PROT), the definitions of the codes or fields used in each database, and the sequence feature types/terms and qualifiers for the nucleotide and protein databases. The second section, "Tools" provides the command line syntax for popular applications such as ReadSeq, MEME/MAST, BLAST, ClustalW, and the EMBOSS suite of analytical tools. The third section, "Appendixes" concentrates on information essential to understanding the individual components that make up a biological sequence. The tables in this section include nucleotide and protein codes, genetic codes, as well as other relevant information. 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. N° de réf. du vendeur LU-9780596004941
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