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.
About the Author
Carolin Loos is currently doing her PhD at the Institute of Computational Biology at the Helmholtz Zentrum Munchen. She is member of the junior research group "Data-driven Computational Modeling".
Book Information
ISBN 9783658132330
Author Carolin Loos
Format Paperback
Page Count 92
Imprint Springer Spektrum
Publisher Springer Fachmedien Wiesbaden
