LEADER 02291nam  2200349z- 450 
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035   $a(CKB)5400000000050625
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/81833
035   $a(oapen)doab81833
035   $a(DNLM)1760378
035   $a(EXLCZ)995400000000050625
100   $a20202205d2019      |y         0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aComputational Biology
210   $aAustralia$cExon Publications$d2019
215   $a1 online resource (194 p.)
311 08$a0-9944381-9-2 
330   $aOur understanding of biology has undergone a revolution in the past 20 years, driven by our ability to capture, store, interrogate and analyze the ever-increasing volumes of 'omics' data. Computational Biology, an integrated approach employing high performance computers, state-of-the art software and algorithms, mathematical modeling and statistical analyses have enabled us to unravel the seemingly impenetrable complexity of biological systems. This book draws together many of the latest cutting-edge developments in the field of Computational Biology. Each chapter draws on the expertise of leading researchers in the field to highlight the utility of specific technologies. The breadth of the text is impressive - from integrative biology in human diseases through the various branches of epigenomics, metabolomics and proteomics to biological sequencing and deep learning. Computational biology approaches for image-based analysis of multicellular spheroids, feature selection using entropy and cellular cryo-electron tomography structural pattern mining are covered. In addition, the key role of statistics in the analysis of high-dimensional multiset omics data and RNA sequencing are discussed in dedicated chapters. This book would have broad appeal to anyone with an interest in cutting edge computational biology.
606   $aMBF$2bicssc
610   $aComputational Biology
615  7$aMBF
700   $aHusi$b Holger$4edt$01288375
702   $aHusi$b Holger$4oth
906   $aBOOK
912   $a9910569197503321
996   $aComputational Biology$93020784
997   $aUNINA