Literature DB >> 30309735

Towards a Quantitative Understanding of Cell Identity.

Zi Ye1, Casim A Sarkar2.   

Abstract

Cells have traditionally been characterized using expression levels of a few proteins that are thought to specify phenotype. This requires a priori selection of proteins, which can introduce descriptor bias, and neglects the wealth of additional molecular information nested within each cell in a population, which often makes these sparse descriptors qualitative. Recently, more unbiased and quantitative cell characterization has been made possible by new high-throughput, information-dense experimental approaches and data-driven computational methods. This review discusses such quantitative descriptors in the context of three central concepts of cell identity: definition, creation, and stability. Collectively, these concepts are essential for constructing quantitative phenotypic landscapes, which will enhance our understanding of cell biology and facilitate cell engineering for research and clinical applications.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  cell phenotype; cellular decision making; computational modeling; high-throughput data analysis; network biology; phenotypic landscape

Mesh:

Substances:

Year:  2018        PMID: 30309735      PMCID: PMC6249108          DOI: 10.1016/j.tcb.2018.09.002

Source DB:  PubMed          Journal:  Trends Cell Biol        ISSN: 0962-8924            Impact factor:   20.808


  66 in total

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Journal:  Mol Syst Biol       Date:  2016-10-20       Impact factor: 11.429

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6.  Phenotypic transitions enacted by simulated microgravity do not alter coherence in gene transcription profile.

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