Journal article
Bayesian statistical learning for big data biology
- Abstract:
- Bayesian statistical learning provides a coherent probabilistic framework for modelling uncertainty in systems. This review describes the theoretical foundations underlying Bayesian statistics and outlines the computational frameworks for implementing Bayesian inference in practice. We then describe the use of Bayesian learning in single-cell biology for the analysis of high-dimensional, large data sets.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 1.0MB, Terms of use)
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- Publisher copy:
- 10.1007/s12551-019-00499-1
Authors
- Publisher:
- Springer
- Journal:
- Biophysical Reviews More from this journal
- Volume:
- 11
- Issue:
- 1
- Pages:
- 95-102
- Publication date:
- 2019-02-07
- Acceptance date:
- 2019-01-08
- DOI:
- EISSN:
-
1867-2469
- ISSN:
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1867-2450
- Pmid:
-
30729409
- Language:
-
English
- Keywords:
- Pubs id:
-
pubs:969585
- UUID:
-
uuid:bc063b4b-8242-4e38-9e5b-cfed58e1e1a4
- Local pid:
-
pubs:969585
- Source identifiers:
-
969585
- Deposit date:
-
2019-03-12
Terms of use
- Copyright holder:
- Yau et al
- Copyright date:
- 2019
- Notes:
- © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
- Licence:
- CC Attribution (CC BY)
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