Overview
- Publication in the field of natural sciences
- Includes supplementary material: sn.pub/extras
Part of the book series: BestMasters (BEST)
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Table of contents (5 chapters)
Keywords
About this book
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.
Authors and Affiliations
About the author
Carolin Loos is currently doing her PhD at the Institute of Computational Biology at the Helmholtz Zentrum München. She is member of the junior research group „Data-driven Computational Modeling“.
Bibliographic Information
Book Title: Analysis of Single-Cell Data
Book Subtitle: ODE Constrained Mixture Modeling and Approximate Bayesian Computation
Authors: Carolin Loos
Series Title: BestMasters
DOI: https://doi.org/10.1007/978-3-658-13234-7
Publisher: Springer Spektrum Wiesbaden
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Fachmedien Wiesbaden 2016
Softcover ISBN: 978-3-658-13233-0Published: 23 March 2016
eBook ISBN: 978-3-658-13234-7Published: 17 March 2016
Series ISSN: 2625-3577
Series E-ISSN: 2625-3615
Edition Number: 1
Number of Pages: XXI, 92
Number of Illustrations: 26 b/w illustrations
Topics: Mathematical and Computational Biology, Computational Mathematics and Numerical Analysis, Computer Appl. in Life Sciences