000			01912cam a2200397 i 4500
001			18198153
003			IIITD
005			20240515020003.0
008			140623t20152015flua b 001 0 eng
010			_a 2014024218
020			_a9781466595002
035			_a(DNLM)101635331
040			_aDNLM/DLC _cDLC _erda _dDLC
042			_apcc
050	0	0	_aQP623 _b.K67 2015
060	1	0	_aQU 58.7
082	0	0	_a572.88 _223 _bKOR-R
100	1		_aKorpelainen, Eija
245	1	0	_aRNA-seq data analysis : _ba practical approach _cEija Korpelainen, Jarno Tuimala, Panu Somervuo, Mikael Huss, Garry Wong.
260			_aLondon : _bCRC Press, _c©2015.
300			_axxiv, 298 p. : _bill. ; _c24 cm.
490	0		_aChapman & Hall/CRC Mathematical and computational biology series
500			_a"A Chapman & Hall book."
504			_aIncludes bibliographical references and index.
520			_a"RNA-seq offers unprecedented information about transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. This self-contained guide enables researchers to examine differential expression at gene, exon, and transcript level and to discover novel genes, transcripts, and whole transcriptomes. Each chapter starts with theoretical background, followed by descriptions of relevant analysis tools. The book also provides examples using command line tools and the R statistical environment. For non-programming scientists, the same examples are covered using open source software with a graphical user interface"--
650	1	2	_aSequence Analysis, RNA _xmethods.
650	1	2	_aTranscriptome.
650	2	2	_aStatistics as Topic.
700	1		_aTuimala, Jarno
700	1		_aSomervuo, Panu
700	1		_aHuss, Mikael
700	1		_aWong, Garry
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK _08
999			_c24806 _d24806