000			02896nam a22003738i 4500
001			CR9780511808982
003			UkCbUP
005			20200124160301.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			101021s2007||||enk o ||1 0|eng|d
020			_a9780511808982 (ebook)
020			_z9780521856034 (hardback)
020			_z9780521671910 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQH438.4.S73 _bC75 2007
082	0	4	_a572.86072 _222
100	1		_aCristianini, Nello, _eauthor.
245	1	0	_aIntroduction to computational genomics : _ba case studies approach / _cNello Cristianini and Matthew W. Hahn.
264		1	_aCambridge : _bCambridge University Press, _c2007.
300			_a1 online resource (xvii, 182 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	0		_aThe first look at a genome : sequence statistics -- All the sequence's men : gene finding -- All in the family : sequence alignment -- The boulevard of broken genes : hidden Markov methods -- Are Neanderthals among us? : variation within and between species -- Fighting HIV : natural selection at the molecular level -- SARS : a post-genomic epidemic : phylogenetic analysis -- Welcome to the hotel Chlamydia : whole genome comparisons -- The genomics of wine-making : analysis of gene expression -- A bed-time story : identification of regulatory sequences.
520			_aWhere 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.
650		0	_aGenomics _xStatistical methods.
650		0	_aComputational biology.
650		0	_aGenomics _xData processing.
700	1		_aHahn, Matthew William, _d1975- _eauthor.
776	0	8	_iPrint version: _z9780521856034
856	4	0	_uhttps://doi.org/10.1017/CBO9780511808982
999			_c520328 _d520326