Analysis of Single-Cell Data : ODE Constrained Mixture Modeling and Approximate Bayesian Computation
Carolin Loos (auth.)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.
Categorie:
Anno:
2016
Edizione:
1
Casa editrice:
Springer Spektrum
Lingua:
english
Pagine:
108
ISBN 10:
3658132345
ISBN 13:
9783658132347
Collana:
BestMasters
File:
PDF, 4.46 MB
IPFS:
,
english, 2016
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