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Systematic Reverse Engineering of Network Topologies: A Case Study of Resettable Bistable Cellular Responses
A focused theme in systems biology is to uncover design principles of biological networks, that is, how specific network structures yield specific systems properties. For this purpose, we have previously developed a reverse engineering procedure to identify network topologies with high likelihood in...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4149494/ https://www.ncbi.nlm.nih.gov/pubmed/25170839 http://dx.doi.org/10.1371/journal.pone.0105833 |
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author | Mondal, Debasish Dougherty, Edward Mukhopadhyay, Abhishek Carbo, Adria Yao, Guang Xing, Jianhua |
author_facet | Mondal, Debasish Dougherty, Edward Mukhopadhyay, Abhishek Carbo, Adria Yao, Guang Xing, Jianhua |
author_sort | Mondal, Debasish |
collection | PubMed |
description | A focused theme in systems biology is to uncover design principles of biological networks, that is, how specific network structures yield specific systems properties. For this purpose, we have previously developed a reverse engineering procedure to identify network topologies with high likelihood in generating desired systems properties. Our method searches the continuous parameter space of an assembly of network topologies, without enumerating individual network topologies separately as traditionally done in other reverse engineering procedures. Here we tested this CPSS (continuous parameter space search) method on a previously studied problem: the resettable bistability of an Rb-E2F gene network in regulating the quiescence-to-proliferation transition of mammalian cells. From a simplified Rb-E2F gene network, we identified network topologies responsible for generating resettable bistability. The CPSS-identified topologies are consistent with those reported in the previous study based on individual topology search (ITS), demonstrating the effectiveness of the CPSS approach. Since the CPSS and ITS searches are based on different mathematical formulations and different algorithms, the consistency of the results also helps cross-validate both approaches. A unique advantage of the CPSS approach lies in its applicability to biological networks with large numbers of nodes. To aid the application of the CPSS approach to the study of other biological systems, we have developed a computer package that is available in Information S1. |
format | Online Article Text |
id | pubmed-4149494 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-41494942014-09-03 Systematic Reverse Engineering of Network Topologies: A Case Study of Resettable Bistable Cellular Responses Mondal, Debasish Dougherty, Edward Mukhopadhyay, Abhishek Carbo, Adria Yao, Guang Xing, Jianhua PLoS One Research Article A focused theme in systems biology is to uncover design principles of biological networks, that is, how specific network structures yield specific systems properties. For this purpose, we have previously developed a reverse engineering procedure to identify network topologies with high likelihood in generating desired systems properties. Our method searches the continuous parameter space of an assembly of network topologies, without enumerating individual network topologies separately as traditionally done in other reverse engineering procedures. Here we tested this CPSS (continuous parameter space search) method on a previously studied problem: the resettable bistability of an Rb-E2F gene network in regulating the quiescence-to-proliferation transition of mammalian cells. From a simplified Rb-E2F gene network, we identified network topologies responsible for generating resettable bistability. The CPSS-identified topologies are consistent with those reported in the previous study based on individual topology search (ITS), demonstrating the effectiveness of the CPSS approach. Since the CPSS and ITS searches are based on different mathematical formulations and different algorithms, the consistency of the results also helps cross-validate both approaches. A unique advantage of the CPSS approach lies in its applicability to biological networks with large numbers of nodes. To aid the application of the CPSS approach to the study of other biological systems, we have developed a computer package that is available in Information S1. Public Library of Science 2014-08-29 /pmc/articles/PMC4149494/ /pubmed/25170839 http://dx.doi.org/10.1371/journal.pone.0105833 Text en © 2014 Mondal et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Mondal, Debasish Dougherty, Edward Mukhopadhyay, Abhishek Carbo, Adria Yao, Guang Xing, Jianhua Systematic Reverse Engineering of Network Topologies: A Case Study of Resettable Bistable Cellular Responses |
title | Systematic Reverse Engineering of Network Topologies: A Case Study of Resettable Bistable Cellular Responses |
title_full | Systematic Reverse Engineering of Network Topologies: A Case Study of Resettable Bistable Cellular Responses |
title_fullStr | Systematic Reverse Engineering of Network Topologies: A Case Study of Resettable Bistable Cellular Responses |
title_full_unstemmed | Systematic Reverse Engineering of Network Topologies: A Case Study of Resettable Bistable Cellular Responses |
title_short | Systematic Reverse Engineering of Network Topologies: A Case Study of Resettable Bistable Cellular Responses |
title_sort | systematic reverse engineering of network topologies: a case study of resettable bistable cellular responses |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4149494/ https://www.ncbi.nlm.nih.gov/pubmed/25170839 http://dx.doi.org/10.1371/journal.pone.0105833 |
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