Carolin Loos

Analysis of Single-Cell Data (eBook, PDF)

ODE Constrained Mixture Modeling and Approximate Bayesian Computation

• Format: PDF

Produktbeschreibung

Carolin 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.

Produktdetails

• Verlag: Springer Fachmedien Wiesbaden GmbH
• Erscheinungstermin: 17. März 2016
• Englisch
• ISBN-13: 9783658132347
• Artikelnr.: 44878956

Autorenporträt

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“.

Inhaltsangabe

Modeling and Parameter Estimation for Single-Cell Data.- ODE Constrained Mixture Modeling for Multivariate Data.- Approximate Bayesian Computation Using Multivariate Statistics.

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Modeling and Parameter Estimation for Single-CellData.- ODE Constrained Mixture Modeling for Multivariate Data.- ApproximateBayesian Computation Using Multivariate Statistics.