LEADER 03405nam 22006255 450 001 9910254061003321 005 20230810213720.0 010 $a3-658-13234-5 024 7 $a10.1007/978-3-658-13234-7 035 $a(CKB)3710000000616478 035 $a(EBL)4454269 035 $a(SSID)ssj0001653989 035 $a(PQKBManifestationID)16433763 035 $a(PQKBTitleCode)TC0001653989 035 $a(PQKBWorkID)14982956 035 $a(PQKB)11256628 035 $a(DE-He213)978-3-658-13234-7 035 $a(MiAaPQ)EBC4454269 035 $a(PPN)192770985 035 $a(EXLCZ)993710000000616478 100 $a20160317d2016 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAnalysis of Single-Cell Data $eODE Constrained Mixture Modeling and Approximate Bayesian Computation /$fby Carolin Loos 205 $a1st ed. 2016. 210 1$aWiesbaden :$cSpringer Fachmedien Wiesbaden :$cImprint: Springer Spektrum,$d2016. 215 $a1 online resource (108 p.) 225 1 $aBestMasters,$x2625-3615 300 $aDescription based upon print version of record. 311 $a3-658-13233-7 320 $aIncludes bibliographical references. 327 $aModeling and Parameter Estimation for Single-Cell Data -- ODE Constrained Mixture Modeling for Multivariate Data -- Approximate Bayesian Computation Using Multivariate Statistics. 330 $aCarolin Loos introduces two novel approaches for the analysis of single-cell data. Both approaches can be used to study cellular heterogeneity and therefore advance a holistic understanding of biological processes. The first method, ODE constrained mixture modeling, enables the identification of subpopulation structures and sources of variability in single-cell snapshot data. The second method estimates parameters of single-cell time-lapse data using approximate Bayesian computation and is able to exploit the temporal cross-correlation of the data as well as lineage information. Contents Modeling and Parameter Estimation for Single-Cell Data ODE Constrained Mixture Modeling for Multivariate Data Approximate Bayesian Computation Using Multivariate Statistics Target Groups Researchers and students in the fields of (bio-)mathematics, statistics, bioinformatics System biologists, biostatisticians, bioinformaticians The Author Carolin Loos is currently doing her PhD at the Institute of Computational Biology at the Helmholtz Zentrum München. She is member of the junior research group ?Data-driven Computational Modeling?. 410 0$aBestMasters,$x2625-3615 606 $aBiomathematics 606 $aMathematics$xData processing 606 $aBioinformatics 606 $aMathematical and Computational Biology 606 $aComputational Mathematics and Numerical Analysis 606 $aComputational and Systems Biology 615 0$aBiomathematics. 615 0$aMathematics$xData processing. 615 0$aBioinformatics. 615 14$aMathematical and Computational Biology. 615 24$aComputational Mathematics and Numerical Analysis. 615 24$aComputational and Systems Biology. 676 $a510 700 $aLoos$b Carolin$4aut$4http://id.loc.gov/vocabulary/relators/aut$0755825 906 $aBOOK 912 $a9910254061003321 996 $aAnalysis of single-cell data$91523145 997 $aUNINA