Analysis of Single-Cell Data:ODE Constrained Mixture Modeling and Approximate Bayesian Computation(BestMasters)

数学史

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作      者
出  版 社
出版时间
2016年03月23日
装      帧
ISBN
9783658132330
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页      码
92
语      种
英文
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图书简介
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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