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Detecting robust time-delayed regulation in Mycobacterium tuberculosis
BACKGROUND: Time delays are often found in gene regulation though most techniques of building gene regulatory networks are not capable of capturing such phenomena. Here we look at the delays in the DNA repair system of Mycobacterium tuberculosis which is unusually slow in the bacteria. We propose a...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2788381/ https://www.ncbi.nlm.nih.gov/pubmed/19958492 http://dx.doi.org/10.1186/1471-2164-10-S3-S28 |
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author | Chaturvedi, Iti Rajapakse, Jagath C |
author_facet | Chaturvedi, Iti Rajapakse, Jagath C |
author_sort | Chaturvedi, Iti |
collection | PubMed |
description | BACKGROUND: Time delays are often found in gene regulation though most techniques of building gene regulatory networks are not capable of capturing such phenomena. Here we look at the delays in the DNA repair system of Mycobacterium tuberculosis which is unusually slow in the bacteria. We propose a method based on a skip-chain model to study this phenomena in gene networks. The Viterbi paths of the underlying Markov chains find the most likely regulatory interactions among genes, taking care of very long delays. Using the derived networks, we discuss the delayed regulations and robustness of the DNA damage seen in the bacterium. RESULTS: We evaluated our method on time-course gene expressions after DNA damage with Mitocyin C. Several time-delayed interactions were observed with our analysis. The presence of hubs in the networks indicates that a small number of transcriptional factors regulate the rest of the system. We demonstrate the use of priors to overcome over-fitting problem in the generation of networks. We compare our results with the gene networks derived with dynamic Bayesian networks (DBN). CONCLUSION: Different transcription networks are active at different stages, and constant feedback and regulation is maintained throughout the activities of a biological pathway. Skip-chain models are capable of capturing, long distant and the time-delayed regulations. Use of a Dirichlet prior over parameters and Gibbs prior over structure can greatly reduce the over-fitting in the new model. |
format | Text |
id | pubmed-2788381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-27883812009-12-04 Detecting robust time-delayed regulation in Mycobacterium tuberculosis Chaturvedi, Iti Rajapakse, Jagath C BMC Genomics Proceedings BACKGROUND: Time delays are often found in gene regulation though most techniques of building gene regulatory networks are not capable of capturing such phenomena. Here we look at the delays in the DNA repair system of Mycobacterium tuberculosis which is unusually slow in the bacteria. We propose a method based on a skip-chain model to study this phenomena in gene networks. The Viterbi paths of the underlying Markov chains find the most likely regulatory interactions among genes, taking care of very long delays. Using the derived networks, we discuss the delayed regulations and robustness of the DNA damage seen in the bacterium. RESULTS: We evaluated our method on time-course gene expressions after DNA damage with Mitocyin C. Several time-delayed interactions were observed with our analysis. The presence of hubs in the networks indicates that a small number of transcriptional factors regulate the rest of the system. We demonstrate the use of priors to overcome over-fitting problem in the generation of networks. We compare our results with the gene networks derived with dynamic Bayesian networks (DBN). CONCLUSION: Different transcription networks are active at different stages, and constant feedback and regulation is maintained throughout the activities of a biological pathway. Skip-chain models are capable of capturing, long distant and the time-delayed regulations. Use of a Dirichlet prior over parameters and Gibbs prior over structure can greatly reduce the over-fitting in the new model. BioMed Central 2009-12-03 /pmc/articles/PMC2788381/ /pubmed/19958492 http://dx.doi.org/10.1186/1471-2164-10-S3-S28 Text en Copyright ©2009 Chaturvedi and Rajapakse; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Chaturvedi, Iti Rajapakse, Jagath C Detecting robust time-delayed regulation in Mycobacterium tuberculosis |
title | Detecting robust time-delayed regulation in Mycobacterium tuberculosis |
title_full | Detecting robust time-delayed regulation in Mycobacterium tuberculosis |
title_fullStr | Detecting robust time-delayed regulation in Mycobacterium tuberculosis |
title_full_unstemmed | Detecting robust time-delayed regulation in Mycobacterium tuberculosis |
title_short | Detecting robust time-delayed regulation in Mycobacterium tuberculosis |
title_sort | detecting robust time-delayed regulation in mycobacterium tuberculosis |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2788381/ https://www.ncbi.nlm.nih.gov/pubmed/19958492 http://dx.doi.org/10.1186/1471-2164-10-S3-S28 |
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