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Beschreibung
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.
ODE Constrained Mixture Modeling and Approximate Bayesian Computation
Details
| Verlag | Springer Fachmedien Wiesbaden GmbH |
| Ersterscheinung | 23. März 2016 |
| Maße | 21 cm x 14.8 cm |
| Gewicht | 162 Gramm |
| Format | Softcover |
| ISBN-13 | 9783658132330 |
| Auflage | 1st ed. 2016 |
| Seiten | 92 |
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