| Literature DB >> 30309735 |
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.Entities:
Keywords: cell phenotype; cellular decision making; computational modeling; high-throughput data analysis; network biology; phenotypic landscape
Mesh:
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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