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@inbook{Thomas:2020:10.1016/B978-0-12-801238-3.11539-9,
author = {Thomas, P},
booktitle = {Systems Medicine: Integrative, Qualitative and Computational Approaches},
doi = {10.1016/B978-0-12-801238-3.11539-9},
editor = {Wolkenhauer},
pages = {45--55},
publisher = {Elsevier, Oxford},
title = {Stochastic Modeling Approaches for Single-Cell Analyses},
url = {http://dx.doi.org/10.1016/B978-0-12-801238-3.11539-9},
year = {2020}
}
TY - CHAP
AB - Single-cell analyses are becoming increasingly important in cell biology and personalized approaches to medicine. Such analyses frequently reveal heterogeneity that exists within and between cells. We give a concise overview of stochastic methods used to analyze non-genetic heterogeneity in models of cell populations and examine several analytical results on the determinants of gene expression noise. We then review models that advanced our understanding of stochastic phenomena in cellular decision making, stem cell differentiation, tissue homoeostasis and cell cycle dynamics.
AU - Thomas,P
DO - 10.1016/B978-0-12-801238-3.11539-9
EP - 55
PB - Elsevier, Oxford
PY - 2020///
SP - 45
TI - Stochastic Modeling Approaches for Single-Cell Analyses
T1 - Systems Medicine: Integrative, Qualitative and Computational Approaches
UR - http://dx.doi.org/10.1016/B978-0-12-801238-3.11539-9
UR - https://www.sciencedirect.com/science/article/pii/B9780128012383115399?via%3Dihub
ER -