Carolin Loos

Analysis of Single-Cell Data

ODE Constrained Mixture Modeling and Approximate Bayesian Computation

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• BestMasters
• Verlag: Springer Fachmedien Wiesbaden / Springer Spektrum / Springer, Berlin
• Artikelnr. des Verlages: 978-3-658-13233-0
• 1st ed. 2016
• Seitenzahl: 116
• Erscheinungstermin: 23. März 2016
• Englisch
• Abmessung: 210mm x 148mm x 7mm
• Gewicht: 162g
• ISBN-13: 9783658132330
• ISBN-10: 3658132337
• Artikelnr.: 44538916

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-CellData.- ODE Constrained Mixture Modeling for Multivariate Data.- ApproximateBayesian Computation Using Multivariate Statistics.

---

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