A Monte Carlo method for in silico modeling and visualization of Waddington’s epigenetic landscape with intermediate details
Waddington’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...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
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2020
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| Online Access: | https://hdl.handle.net/10356/144897 |
| _version_ | 1811681352863449088 |
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| author | Zhang, Xiaomeng Chong, Ket Hing Zhu, Lin Zheng, Jie |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Zhang, Xiaomeng Chong, Ket Hing Zhu, Lin Zheng, Jie |
| author_sort | Zhang, Xiaomeng |
| collection | NTU |
| description | Waddington’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. |
| first_indexed | 2024-10-01T03:39:35Z |
| format | Journal Article |
| id | ntu-10356/144897 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:39:35Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1448972021-02-05T01:57:47Z A Monte Carlo method for in silico modeling and visualization of Waddington’s epigenetic landscape with intermediate details Zhang, Xiaomeng Chong, Ket Hing Zhu, Lin Zheng, Jie School of Computer Science and Engineering Biomedical Informatics Lab Engineering::Computer science and engineering Waddington’s Epigenetic Landscape Monte Carlo Waddington’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. Ministry of Education (MOE) Accepted version This 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. 2020-12-02T07:53:36Z 2020-12-02T07:53:36Z 2020 Journal Article Zhang, 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.2020.104275 0303-2647 https://hdl.handle.net/10356/144897 10.1016/j.biosystems.2020.104275 198 en Biosystems © 2020 Elsevier B.V. All rights reserved. This paper was published in Biosystems and is made available with permission of Elsevier B.V. application/pdf |
| spellingShingle | Engineering::Computer science and engineering Waddington’s Epigenetic Landscape Monte Carlo Zhang, Xiaomeng Chong, Ket Hing Zhu, Lin Zheng, Jie A Monte Carlo method for in silico modeling and visualization of Waddington’s epigenetic landscape with intermediate details |
| title | A Monte Carlo method for in silico modeling and visualization of Waddington’s epigenetic landscape with intermediate details |
| title_full | A Monte Carlo method for in silico modeling and visualization of Waddington’s epigenetic landscape with intermediate details |
| title_fullStr | A Monte Carlo method for in silico modeling and visualization of Waddington’s epigenetic landscape with intermediate details |
| title_full_unstemmed | A Monte Carlo method for in silico modeling and visualization of Waddington’s epigenetic landscape with intermediate details |
| title_short | A Monte Carlo method for in silico modeling and visualization of Waddington’s epigenetic landscape with intermediate details |
| title_sort | monte carlo method for in silico modeling and visualization of waddington s epigenetic landscape with intermediate details |
| topic | Engineering::Computer science and engineering Waddington’s Epigenetic Landscape Monte Carlo |
| url | https://hdl.handle.net/10356/144897 |
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