Analysis of Single-Cell Data: ODE Constrained Mixture Modeling and Approximate Bayesian Computation (1st ed. 2016) (BestMasters)
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- Synopsis
- 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.
- Copyright:
- 2016
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783658132347
- Related ISBNs:
- 9783658132330
- Publisher:
- Springer Fachmedien Wiesbaden
- Date of Addition:
- 10/07/19
- Copyrighted By:
- N/A
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Science, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.