Analysis of Single-Cell Data: Ode Constrained Mixture Modeling and Approximate Bayesian Computation 2016 Edition Contributor(s): Loos, Carolin (Author) |
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ISBN: 3658132337 ISBN-13: 9783658132330 Publisher: Springer Spektrum
Binding Type: Paperback - See All Available Formats & Editions Published: March 2016 Click for more in this series: Bestmasters |
Additional Information |
BISAC Categories: - Mathematics | Applied - Mathematics | Counting & Numeration - Science | Life Sciences - General |
Dewey: 518 |
Series: Bestmasters |
Physical Information: 0.28" H x 5.83" W x 8.27" L (0.35 lbs) 92 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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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