Information-theoretic approaches to understanding stem cell variability
Information-theoretic approaches to understanding stem cell variability
Purpose of Review: the purpose of this study is to outline how ideas from information theory may be used to analyze single-cell data and better understand stem cell behavior.
Recent Findings: recent technological breakthroughs in single-cell profiling have made it possible to interrogate cell–cell variability in a multitude of contexts, including the role it plays in stem cell dynamics. Here we review how measures from information theory are being used to extract biological meaning from the complex, high-dimensional, and noisy datasets that arise from single-cell profiling experiments. We also discuss how concepts linking information theory and statistical mechanics are being used to provide insight into cellular identity, variability, and dynamics.
Summary: we provide a brief introduction to some basic notions from information theory and how they may be used to understand stem cell identities at the single-cell level. We also discuss how work in this area might develop in the near future.
225-231
Smith, Rosanna
1fe5586f-92e9-4658-bd55-cd3eaa176b66
Macarthur, Benjamin
2c0476e7-5d3e-4064-81bb-104e8e88bb6b
September 2017
Smith, Rosanna
1fe5586f-92e9-4658-bd55-cd3eaa176b66
Macarthur, Benjamin
2c0476e7-5d3e-4064-81bb-104e8e88bb6b
Smith, Rosanna and Macarthur, Benjamin
(2017)
Information-theoretic approaches to understanding stem cell variability.
Current Stem Cell Reports, 3 (3), .
(doi:10.1007/s40778-017-0093-5).
Abstract
Purpose of Review: the purpose of this study is to outline how ideas from information theory may be used to analyze single-cell data and better understand stem cell behavior.
Recent Findings: recent technological breakthroughs in single-cell profiling have made it possible to interrogate cell–cell variability in a multitude of contexts, including the role it plays in stem cell dynamics. Here we review how measures from information theory are being used to extract biological meaning from the complex, high-dimensional, and noisy datasets that arise from single-cell profiling experiments. We also discuss how concepts linking information theory and statistical mechanics are being used to provide insight into cellular identity, variability, and dynamics.
Summary: we provide a brief introduction to some basic notions from information theory and how they may be used to understand stem cell identities at the single-cell level. We also discuss how work in this area might develop in the near future.
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Accepted/In Press date: 13 June 2017
e-pub ahead of print date: 13 July 2017
Published date: September 2017
Identifiers
Local EPrints ID: 413652
URI: http://eprints.soton.ac.uk/id/eprint/413652
ISSN: 2198-7866
PURE UUID: 24afdda2-ed50-44cf-9d74-04f84bf0244a
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Date deposited: 31 Aug 2017 16:31
Last modified: 16 Mar 2024 05:41
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Author:
Rosanna Smith
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