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Integration of curated databases to identify genotype-phenotype associations
BACKGROUND: The ability to rapidly characterize an unknown microorganism is critical in both responding to infectious disease and biodefense. To do this, we need some way of anticipating an organism's phenotype based on the molecules encoded by its genome. However, the link between molecular co...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2006
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1630430/ https://www.ncbi.nlm.nih.gov/pubmed/17038185 http://dx.doi.org/10.1186/1471-2164-7-257 |
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author | Goh, Chern-Sing Gianoulis, Tara A Liu, Yang Li, Jianrong Paccanaro, Alberto Lussier, Yves A Gerstein, Mark |
author_facet | Goh, Chern-Sing Gianoulis, Tara A Liu, Yang Li, Jianrong Paccanaro, Alberto Lussier, Yves A Gerstein, Mark |
author_sort | Goh, Chern-Sing |
collection | PubMed |
description | BACKGROUND: The ability to rapidly characterize an unknown microorganism is critical in both responding to infectious disease and biodefense. To do this, we need some way of anticipating an organism's phenotype based on the molecules encoded by its genome. However, the link between molecular composition (i.e. genotype) and phenotype for microbes is not obvious. While there have been several studies that address this challenge, none have yet proposed a large-scale method integrating curated biological information. Here we utilize a systematic approach to discover genotype-phenotype associations that combines phenotypic information from a biomedical informatics database, GIDEON, with the molecular information contained in National Center for Biotechnology Information's Clusters of Orthologous Groups database (NCBI COGs). RESULTS: Integrating the information in the two databases, we are able to correlate the presence or absence of a given protein in a microbe with its phenotype as measured by certain morphological characteristics or survival in a particular growth media. With a 0.8 correlation score threshold, 66% of the associations found were confirmed by the literature and at a 0.9 correlation threshold, 86% were positively verified. CONCLUSION: Our results suggest possible phenotypic manifestations for proteins biochemically associated with sugar metabolism and electron transport. Moreover, we believe our approach can be extended to linking pathogenic phenotypes with functionally related proteins. |
format | Text |
id | pubmed-1630430 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-16304302006-11-06 Integration of curated databases to identify genotype-phenotype associations Goh, Chern-Sing Gianoulis, Tara A Liu, Yang Li, Jianrong Paccanaro, Alberto Lussier, Yves A Gerstein, Mark BMC Genomics Methodology Article BACKGROUND: The ability to rapidly characterize an unknown microorganism is critical in both responding to infectious disease and biodefense. To do this, we need some way of anticipating an organism's phenotype based on the molecules encoded by its genome. However, the link between molecular composition (i.e. genotype) and phenotype for microbes is not obvious. While there have been several studies that address this challenge, none have yet proposed a large-scale method integrating curated biological information. Here we utilize a systematic approach to discover genotype-phenotype associations that combines phenotypic information from a biomedical informatics database, GIDEON, with the molecular information contained in National Center for Biotechnology Information's Clusters of Orthologous Groups database (NCBI COGs). RESULTS: Integrating the information in the two databases, we are able to correlate the presence or absence of a given protein in a microbe with its phenotype as measured by certain morphological characteristics or survival in a particular growth media. With a 0.8 correlation score threshold, 66% of the associations found were confirmed by the literature and at a 0.9 correlation threshold, 86% were positively verified. CONCLUSION: Our results suggest possible phenotypic manifestations for proteins biochemically associated with sugar metabolism and electron transport. Moreover, we believe our approach can be extended to linking pathogenic phenotypes with functionally related proteins. BioMed Central 2006-10-12 /pmc/articles/PMC1630430/ /pubmed/17038185 http://dx.doi.org/10.1186/1471-2164-7-257 Text en Copyright © 2006 Goh et al; 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 | Methodology Article Goh, Chern-Sing Gianoulis, Tara A Liu, Yang Li, Jianrong Paccanaro, Alberto Lussier, Yves A Gerstein, Mark Integration of curated databases to identify genotype-phenotype associations |
title | Integration of curated databases to identify genotype-phenotype associations |
title_full | Integration of curated databases to identify genotype-phenotype associations |
title_fullStr | Integration of curated databases to identify genotype-phenotype associations |
title_full_unstemmed | Integration of curated databases to identify genotype-phenotype associations |
title_short | Integration of curated databases to identify genotype-phenotype associations |
title_sort | integration of curated databases to identify genotype-phenotype associations |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1630430/ https://www.ncbi.nlm.nih.gov/pubmed/17038185 http://dx.doi.org/10.1186/1471-2164-7-257 |
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