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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.
| Autorius: | Carolin Loos |
| Serija: | BestMasters |
| Leidėjas: | Springer Fachmedien Wiesbaden |
| Išleidimo metai: | 2016 |
| Knygos puslapių skaičius: | 116 |
| ISBN-10: | 3658132337 |
| ISBN-13: | 9783658132330 |
| Formatas: | 210 x 148 x 7 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Analysis of Single-Cell Data: ODE Constrained Mixture Modeling and Approximate Bayesian Computation“
