ISBN: 9783658132330 - analysis of single-cell data: ode constrained mixture modeling and approximate bayesian computation (bestmasters) (13 resultados)

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Carolin Loos introduces two novel approaches for theanalysis of single-cell data. Both approaches can be used to study cellularheterogeneity and therefore advance a holistic understanding of biologicalprocesses. The first method, ODE constrained mixture modeling, enables theidentification of subpopulation structures and sources of variability in single-cellsnapshot data. The second method estimates parameters of single-cell time-lapsedata using approximate Bayesian computation and is able to exploit the temporalcross-correlation of the data as well as lineage information.…

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Carolin Loos introduces two novel approaches for theanalysis of single-cell data. Both approaches can be used to study cellularheterogeneity and therefore advance a holistic understanding of biologicalprocesses. The first method, ODE constrained mixture modeling, enables theidentification of subpopulation structures and sources of variability in single-cellsnapshot data. The second method estimates parameters of single-cell time-lapsedata using approximate Bayesian computation and is able to exploit the temporalcross-correlation of the data as well as lineage information. 116 pp. Englisch.…

Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Publication in the field of natural sciencesCarolin Loos is currently doing her PhD at the Institute ofComputational Biology at the Helmholtz Zentrum Muenchen. She is member of thejunior research group Data-driven Computational Modeling .&nbsp. …

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Carolin Loos introduces two novel approaches for theanalysis of single-cell data. Both approaches can be used to study cellularheterogeneity and therefore advance a holistic understanding of biologicalprocesses. The first method, ODE constrained mixture modeling, enables theidentification of subpopulation structures and sources of variability in single-cellsnapshot data. The second method estimates parameters of single-cell time-lapsedata using approximate Bayesian computation and is able to exploit the temporalcross-correlation of the data as well as lineage information.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 116 pp. Englisch.…