LEADER 03688nam 2200721 450 001 9910465346503321 005 20200520144314.0 010 $a1-4008-6526-3 024 7 $a10.1515/9781400865260 035 $a(CKB)3710000000222325 035 $a(EBL)1756203 035 $a(OCoLC)888743988 035 $a(SSID)ssj0001332935 035 $a(PQKBManifestationID)11795618 035 $a(PQKBTitleCode)TC0001332935 035 $a(PQKBWorkID)11376367 035 $a(PQKB)10798329 035 $a(MiAaPQ)EBC1756203 035 $a(DE-B1597)447423 035 $a(OCoLC)888349051 035 $a(OCoLC)979954523 035 $a(DE-B1597)9781400865260 035 $a(Au-PeEL)EBL1756203 035 $a(CaPaEBR)ebr10910144 035 $a(CaONFJC)MIL637580 035 $a(EXLCZ)993710000000222325 100 $a20140829h20072007 uy 0 101 0 $aeng 135 $aur|nu---|u||u 181 $ctxt 182 $cc 183 $acr 200 10$aGenomic signal processing /$fIlya Shmulevich and Edward R. Dougherty 210 1$aPrinceton, New Jersey ;$aOxfordshire, England :$cPrinceton University Press,$d2007. 210 4$dİ2007 215 $a1 online resource (314 p.) 225 1 $aPrinceton Series in Applied Mathematics 300 $aDescription based upon print version of record. 311 0 $a1-322-06329-X 311 0 $a0-691-11762-4 320 $aIncludes bibliographical references and index. 327 $tFront matter --$tContents --$tPreface --$tChapter One. Biological Foundations --$tChapter Two. Deterministic Models of Gene Networks --$tChapter Three. Stochastic Models of Gene Networks --$tChapter Four. Classification --$tChapter Five. Regularization --$tChapter Six. Clustering --$tIndex 330 $aGenomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathematical definitions and propositions for the main elements of GSP and by paying attention to the validity of models relative to the data. Ilya Shmulevich and Edward Dougherty cover real-world situations and explain their mathematical modeling in relation to systems biology and systems medicine. Genomic Signal Processing makes a major contribution to computational biology, systems biology, and translational genomics by providing a self-contained explanation of the fundamental mathematical issues facing researchers in four areas: classification, clustering, network modeling, and network intervention. 410 0$aPrinceton series in applied mathematics. 606 $aCellular signal transduction 606 $aGenetic regulation 606 $aGenomics$xMathematical models 606 $aGene regulatory networks 608 $aElectronic books. 615 0$aCellular signal transduction. 615 0$aGenetic regulation. 615 0$aGenomics$xMathematical models. 615 0$aGene regulatory networks. 676 $a572.8/65 700 $aShmulevich$b Ilya$f1969-$0474514 702 $aDougherty$b Edward R. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910465346503321 996 $aGenomic signal processing$91747442 997 $aUNINA