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dc.contributor.authorZhang, Xiaomengen_US
dc.contributor.authorChong, Ket Hingen_US
dc.contributor.authorZhu, Linen_US
dc.contributor.authorZheng, Jieen_US
dc.identifier.citationZhang, X., Chong, K. H., Zhu, L., & Zheng, J. (2020). A Monte Carlo method for in silico modeling and visualization of Waddington’s epigenetic landscape with intermediate details. Biosystems, 198, 104275-. doi:10.1016/j.biosystems.2020.104275en_US
dc.description.abstractWaddington’s epigenetic landscape is a classic metaphor for describing the cellular dynamics during the development modulated by gene regulation. Quantifying Waddington’s epigenetic landscape by mathematical modeling would be useful for understanding the mechanisms of cell fate determination. A few computational methods have been proposed for quantitative modeling of landscape; however, to model and visualize the landscape of a high dimensional gene regulatory system with realistic details is still challenging. Here, we propose a Monte Carlo method for modeling the Waddington’s epigenetic landscape of a gene regulatory network (GRN). The method estimates the probability distribution of cellular states by collecting a large number of time-course simulations with random initial conditions. By projecting all the trajectories into a2-dimensional plane of dimensions𝑖and𝑗, we can approximately calculate the quasi-potential𝑈(𝑥𝑖,𝑥𝑗,∗) = −ln𝑃(𝑥𝑖,𝑥𝑗,∗), where𝑃(𝑥𝑖,𝑥𝑗,∗)is the estimated probability of an equilibrium steady state or a non-equilibrium state. Compared to the state-of-the-art methods, our Monte Carlo method can quantify the global potential landscape (or emergence behavior) of GRN for a high dimensional system. The potential landscapes show that not only attractors represent stability, but the paths between attractors are also part of the stability or robustness of biological systems. We demonstrate the novelty and reliability of our method by plotting the potential landscapes of a few published models of GRN.en_US
dc.description.sponsorshipMinistry of Education (MOE)en_US
dc.rights© 2020 Elsevier B.V. All rights reserved. This paper was published in Biosystems and is made available with permission of Elsevier B.V.en_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleA Monte Carlo method for in silico modeling and visualization of Waddington’s epigenetic landscape with intermediate detailsen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.contributor.researchBiomedical Informatics Laben_US
dc.description.versionAccepted versionen_US
dc.subject.keywordsWaddington’s Epigenetic Landscapeen_US
dc.subject.keywordsMonte Carloen_US
dc.description.acknowledgementThis work was supported by the MOE AcRF Tier 1 grant (2015-T1-002-094), MOE AcRF Tier 1 Seed Grant on Complexity (RGC 2/13,M4011101.020), and MOE AcRF Tier 2 Grant (ARC39/13, MOE2013-T2-1-079), Ministry of Education Singapore, and the start-up grant of ShanghaiTech University, Shanghai, China.en_US
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