Bayesian statistical learning for big data biology

Christopher Yau; Kieran Campbell

doi:10.1007/s12551-019-00499-1

Bayesian statistical learning for big data biology

Christopher Yau, Kieran Campbell

Research output: Contribution to journal › Review article › peer-review

8 Citations (Scopus)

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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.

Original language	English
Pages (from-to)	95-102
Number of pages	8
Journal	Biophysical Reviews
Volume	11
Early online date	7 Feb 2019
DOIs	https://doi.org/10.1007/s12551-019-00499-1
Publication status	E-pub ahead of print - 7 Feb 2019

Keywords

Bayesian
Computational biology
Statistical modelling

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Yau_Campbell_2019_Bayesian_statistical_learning_for_big_data_biology_Biophysical_ReviewsFinal published version, 1.02 MBLicence: Creative Commons: Attribution (CC BY)

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Bayesian statistical learning for big data biology

Abstract

Keywords

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