An accessible guide to learning the key features of Unix and Perl, written with the non-programmer in mind.
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Keith Bradnam is a project scientist in the Genome Center at the University of California, Davis. He has extensive experience working with model organism databases and spent four years as a project leader at WormBase, helping to develop this important bioinformatics resource.
Ian Korf is an Associate Professor in Molecular and Cellular Biology at the University of California, Davis. His research seeks to understand structure and function in genomic DNA. He has developed new tools for gene prediction, co-authored the only book devoted to BLAST and helped in the development of BioPerl.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. Your research has generated gigabytes of data and now you need to analyse it. You hate using spreadsheets but it is all you know, so what else can you do? This book will transform how you work with large and complex data sets, teaching you powerful programming tools for slicing and dicing data to suit your needs. Written in a fun and accessible style, this step-by-step guide will inspire and inform non-programmers about the essential aspects of Unix and Perl. It shows how, with just a little programming knowledge, you can write programs that could save you hours, or even days. No prior experience is required and new concepts are introduced using numerous code examples that you can try out for yourself. Going beyond the basics, the authors touch upon many broader topics that will help those new to programming, including debugging and how to write in a good programming style. Follow the book on Twitter at: atunixandperl. Written in a fun, accessible style, this step-by-step guide teaches non-programmers the key aspects of Unix and Perl. No prior experience is required and new concepts are introduced using code examples for readers to try themselves. Essential reading for those who want to work more effectively with large data sets. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781107000681
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