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Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses

BACKGROUND: Pathway analysis has been widely used to gain insight into essential mechanisms of the response to myocardial infarction (MI). Currently, there exist multiple pathway databases that organize molecular datasets and manually curate pathway maps for biological interpretation at varying form...

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Autores principales: Nguyen, Nguyen T, Lindsey, Merry L, Jin, Yu-Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4474415/
https://www.ncbi.nlm.nih.gov/pubmed/26100218
http://dx.doi.org/10.1186/1471-2164-16-S7-S18
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author Nguyen, Nguyen T
Lindsey, Merry L
Jin, Yu-Fang
author_facet Nguyen, Nguyen T
Lindsey, Merry L
Jin, Yu-Fang
author_sort Nguyen, Nguyen T
collection PubMed
description BACKGROUND: Pathway analysis has been widely used to gain insight into essential mechanisms of the response to myocardial infarction (MI). Currently, there exist multiple pathway databases that organize molecular datasets and manually curate pathway maps for biological interpretation at varying forms of organization. However, inconsistencies among different databases in pathway descriptions, frequently due to conflicting results in the literature, can generate incorrect interpretations. Furthermore, although pathway analysis software provides detailed images of interactions among molecules, it does not exhibit how pathways interact with one another or with other biological processes under specific conditions. METHODS: We propose a novel method to standardize descriptions of enriched pathways for a set of genes/proteins using Gene Ontology terms. We used this method to examine the relationships among pathways and biological processes for a set of condition-specific genes/proteins, represented as a functional biological pathway-process network. We applied this algorithm to a set of 613 MI-specific proteins we previously identified. RESULTS: A total of 96 pathways from Biocarta, KEGG, and Reactome, and 448 Gene Ontology Biological Processes were enriched with these 613 proteins. The pathways were represented as Boolean functions of biological processes, delivering an interactive scheme to organize enriched information with an emphasis on involvement of biological processes in pathways. We extracted a network focusing on MI to demonstrate that tyrosine phosphorylation of Signal Transducer and Activator of Transcription (STAT) protein, positive regulation of collagen metabolic process, coagulation, and positive/negative regulation of blood coagulation have immediate impacts on the MI response. CONCLUSIONS: Our method organized biological processes and pathways in an unbiased approach to provide an intuitive way to identify biological properties of pathways under specific conditions. Pathways from different databases have similar descriptions yet diverse biological processes, indicating variation in their ability to share similar functional characteristics. The coverages of pathways can be expanded with the incorporation of more biological processes, predicting involvement of protein members in pathways. Further, detailed analyses of the functional biological pathway-process network will allow researchers and scientists to explore critical routes in biological systems in the progression of disease.
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spelling pubmed-44744152015-06-25 Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses Nguyen, Nguyen T Lindsey, Merry L Jin, Yu-Fang BMC Genomics Research BACKGROUND: Pathway analysis has been widely used to gain insight into essential mechanisms of the response to myocardial infarction (MI). Currently, there exist multiple pathway databases that organize molecular datasets and manually curate pathway maps for biological interpretation at varying forms of organization. However, inconsistencies among different databases in pathway descriptions, frequently due to conflicting results in the literature, can generate incorrect interpretations. Furthermore, although pathway analysis software provides detailed images of interactions among molecules, it does not exhibit how pathways interact with one another or with other biological processes under specific conditions. METHODS: We propose a novel method to standardize descriptions of enriched pathways for a set of genes/proteins using Gene Ontology terms. We used this method to examine the relationships among pathways and biological processes for a set of condition-specific genes/proteins, represented as a functional biological pathway-process network. We applied this algorithm to a set of 613 MI-specific proteins we previously identified. RESULTS: A total of 96 pathways from Biocarta, KEGG, and Reactome, and 448 Gene Ontology Biological Processes were enriched with these 613 proteins. The pathways were represented as Boolean functions of biological processes, delivering an interactive scheme to organize enriched information with an emphasis on involvement of biological processes in pathways. We extracted a network focusing on MI to demonstrate that tyrosine phosphorylation of Signal Transducer and Activator of Transcription (STAT) protein, positive regulation of collagen metabolic process, coagulation, and positive/negative regulation of blood coagulation have immediate impacts on the MI response. CONCLUSIONS: Our method organized biological processes and pathways in an unbiased approach to provide an intuitive way to identify biological properties of pathways under specific conditions. Pathways from different databases have similar descriptions yet diverse biological processes, indicating variation in their ability to share similar functional characteristics. The coverages of pathways can be expanded with the incorporation of more biological processes, predicting involvement of protein members in pathways. Further, detailed analyses of the functional biological pathway-process network will allow researchers and scientists to explore critical routes in biological systems in the progression of disease. BioMed Central 2015-06-11 /pmc/articles/PMC4474415/ /pubmed/26100218 http://dx.doi.org/10.1186/1471-2164-16-S7-S18 Text en Copyright © 2015 Nguyen et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Nguyen, Nguyen T
Lindsey, Merry L
Jin, Yu-Fang
Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses
title Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses
title_full Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses
title_fullStr Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses
title_full_unstemmed Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses
title_short Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses
title_sort systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4474415/
https://www.ncbi.nlm.nih.gov/pubmed/26100218
http://dx.doi.org/10.1186/1471-2164-16-S7-S18
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