Analysis of Single-Cell Data - ODE Constrained Mixture Modeling and Approximate Bayesian Computation

Carolin Loos introduces two novel approaches for theanalysis of single-cell data. Both approaches can be used to study cellularheterogeneity and therefore advance a holistic understanding of biologicalprocesses. The first method, ODE constrained mixture modeling, enables theidentification of subpopulation structures and sources of variability in single-cellsnapshot data. The second method estimates parameters of single-cell time-lapsedata using approximate Bayesian computation and is able to exploit the temporalcross-correlation of the data as well as lineage information. 

List of contents

Modeling and Parameter Estimation for Single-CellData.- ODE Constrained Mixture Modeling for Multivariate Data.- ApproximateBayesian Computation Using Multivariate Statistics.

Product details

• Authors: Carolin Loos
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 23.03.2016
• EAN: 9783658132330
• ISBN: 978-3-658-13233-0
• No. of pages: 92
• Dimensions: 150 mm x 210 mm x 5 mm
• Weight: 162 g
• Illustrations: XXI, 92 p. 26 illus.
• Series: BestMasters
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Miscellaneous; C, bioinformatics, Biology, life sciences, Mathematics and Statistics, Computational Mathematics and Numerical Analysis, Computer mathematics, Numerical analysis, Information technology: general issues, Computational and Systems Biology, Biomathematics, Mathematical and Computational Biology, Computational biology, Computer Appl. in Life Sciences