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100   $a20120111d2011      uy         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 00$aApplied statistics for network biology $emethods in system biology /$fedited by Matthias Dehmer ... [et al.]
210   $aWeinheim, Germany $cWiley-Blackwell$d2011
215   $a1 online resource (480 p.)
225 1 $aQuantitative and network biology ;$vv. 1
300   $aDescription based upon print version of record.
311 08$a9783527327508 
311 08$a3527327509 
320   $aIncludes bibliographical references and index.
327   $apt. 1. Modeling, simulation, and meaning of gene networks -- pt. 2. Inference of gene networks -- pt. 3. Analysis of gene networks -- pt. 4. Systems approach to diseases.
330   $aThe book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, researchers are trying to analyze as many data as possible in a given biological system (such as a cell or an organ). The appropriate statistical evaluation of these large scale data is critical for the correct interpretation and different experimental approaches require different approaches for the statistical analysis of these data. This book is written by biostatisticians and mathemati
410  0$aQuantitative and network biology ;$vv. 1.
606   $aSystems biology$xStatistical methods
606   $aGenomics
606   $aComputational biology
606   $aBioinformatics
615  0$aSystems biology$xStatistical methods.
615  0$aGenomics.
615  0$aComputational biology.
615  0$aBioinformatics.
676   $a570.727
701   $aDehmer$b Matthias$0860612
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910131029103321
996   $aApplied statistics for network biology$91920474
997   $aUNINA