Isbn: 9780521671910 - introduction to computational genomics: a case studies approach (5 Ergebnisse)

paperback. Zustand: Good. minor wear and creasing.

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Zustand: New. In English.

Zustand: New. Self-contained and entertaining introduction to computational genomics, using a case-studies approach with Matlab demos. Num Pages: 202 pages, 51 b/w illus. 6 colour illus. 12 tables 32 exercises. BIC Classification: PSAK; UY. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 244 x 189 x 11. Weight in Grams: 388. A Case Studies Approach. 200 pages, 51 b/w illus. 6 colour illus. 12 tables 32 exercises. Self-contained and entertaining introduction to computational genomics, using a case-studies approach with Matlab demos. Cateogry: (P) Professional & Vocational; (U) Tertiary Education (US: College). BIC Classification: PSAK; UY. Dimension: 244 x 189 x 11. Weight: 440. . 2007. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Where did SARS come from Have we inherited genes from Neanderthals How do plants use their internal clock The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many universities are introducing courses to train the next generation of bioinformaticians: biologists fluent in mathematics and computer science, and data analysts familiar with biology. This readable and entertaining book, based on successful taught courses, provides a roadmap to navigate entry to this field. It guides the reader through key achievements of bioinformatics, using a hands-on approach. Statistical sequence analysis, sequence alignment, hidden Markov models, gene and motif finding and more, are introduced in a rigorous yet accessible way. A companion website provides the reader with Matlab-related software tools for reproducing the steps demonstrated in the book.…