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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Analysis of Single-Cell Data: Ode Constrained Mixture Modeling and Approximate Bayesian Computation

Analysis of Single-Cell Data: Ode Constrained Mixture Modeling and Approximate Bayesian Computation

Loos, Carolin

Paperback

Series: Bestmasters

BiologyGeneral Mathematics

ISBN10: 3658132337
ISBN13: 9783658132330
Publisher: Springer Spektrum
Published: Mar 23 2016
Pages: 92
Weight: 0.35
Height: 0.28 Width: 5.83 Depth: 8.27
Language: English

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.

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