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Analysis of Single-Cell Data: ODE Constrained Mixture Modeling and Approximate Bayesian Computation (BestMasters) - Softcover
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.
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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“.
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- PublisherSpringer Spektrum
- Publication date2016
- ISBN 10 3658132337
- ISBN 13 9783658132330
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages113
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Analysis of Single-Cell Data
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ISBN 10: 3658132337
ISBN 13: 9783658132330
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 116 pp. Englisch. Seller Inventory # 9783658132330
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Analysis of Single-Cell Data : ODE Constrained Mixture Modeling and Approximate Bayesian Computation
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783658132330
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Analysis of Single-cell Data: Ode Constrained Mixture Modeling and Approximate Bayesian Computation
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