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GO-2D: identifying 2-dimensional cellular-localized functional modules in Gene Ontology
BACKGROUND: Rapid progress in high-throughput biotechnologies (e.g. microarrays) and exponential accumulation of gene functional knowledge make it promising for systematic understanding of complex human diseases at functional modules level. Based on Gene Ontology, a large number of automatic tools h...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1794235/ https://www.ncbi.nlm.nih.gov/pubmed/17250772 http://dx.doi.org/10.1186/1471-2164-8-30 |
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author | Zhu, Jing Wang, Jing Guo, Zheng Zhang, Min Yang, Da Li, Yanhui Wang, Dong Xiao, Guohua |
author_facet | Zhu, Jing Wang, Jing Guo, Zheng Zhang, Min Yang, Da Li, Yanhui Wang, Dong Xiao, Guohua |
author_sort | Zhu, Jing |
collection | PubMed |
description | BACKGROUND: Rapid progress in high-throughput biotechnologies (e.g. microarrays) and exponential accumulation of gene functional knowledge make it promising for systematic understanding of complex human diseases at functional modules level. Based on Gene Ontology, a large number of automatic tools have been developed for the functional analysis and biological interpretation of the high-throughput microarray data. RESULTS: Different from the existing tools such as Onto-Express and FatiGO, we develop a tool named GO-2D for identifying 2-dimensional functional modules based on combined GO categories. For example, it refines biological process categories by sorting their genes into different cellular component categories, and then extracts those combined categories enriched with the interesting genes (e.g., the differentially expressed genes) for identifying the cellular-localized functional modules. Applications of GO-2D to the analyses of two human cancer datasets show that very specific disease-relevant processes can be identified by using cellular location information. CONCLUSION: For studying complex human diseases, GO-2D can extract functionally compact and detailed modules such as the cellular-localized ones, characterizing disease-relevant modules in terms of both biological processes and cellular locations. The application results clearly demonstrate that 2-dimensional approach complementary to current 1-dimensional approach is powerful for finding modules highly relevant to diseases. |
format | Text |
id | pubmed-1794235 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-17942352007-02-07 GO-2D: identifying 2-dimensional cellular-localized functional modules in Gene Ontology Zhu, Jing Wang, Jing Guo, Zheng Zhang, Min Yang, Da Li, Yanhui Wang, Dong Xiao, Guohua BMC Genomics Software BACKGROUND: Rapid progress in high-throughput biotechnologies (e.g. microarrays) and exponential accumulation of gene functional knowledge make it promising for systematic understanding of complex human diseases at functional modules level. Based on Gene Ontology, a large number of automatic tools have been developed for the functional analysis and biological interpretation of the high-throughput microarray data. RESULTS: Different from the existing tools such as Onto-Express and FatiGO, we develop a tool named GO-2D for identifying 2-dimensional functional modules based on combined GO categories. For example, it refines biological process categories by sorting their genes into different cellular component categories, and then extracts those combined categories enriched with the interesting genes (e.g., the differentially expressed genes) for identifying the cellular-localized functional modules. Applications of GO-2D to the analyses of two human cancer datasets show that very specific disease-relevant processes can be identified by using cellular location information. CONCLUSION: For studying complex human diseases, GO-2D can extract functionally compact and detailed modules such as the cellular-localized ones, characterizing disease-relevant modules in terms of both biological processes and cellular locations. The application results clearly demonstrate that 2-dimensional approach complementary to current 1-dimensional approach is powerful for finding modules highly relevant to diseases. BioMed Central 2007-01-24 /pmc/articles/PMC1794235/ /pubmed/17250772 http://dx.doi.org/10.1186/1471-2164-8-30 Text en Copyright © 2007 Zhu 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 | Software Zhu, Jing Wang, Jing Guo, Zheng Zhang, Min Yang, Da Li, Yanhui Wang, Dong Xiao, Guohua GO-2D: identifying 2-dimensional cellular-localized functional modules in Gene Ontology |
title | GO-2D: identifying 2-dimensional cellular-localized functional modules in Gene Ontology |
title_full | GO-2D: identifying 2-dimensional cellular-localized functional modules in Gene Ontology |
title_fullStr | GO-2D: identifying 2-dimensional cellular-localized functional modules in Gene Ontology |
title_full_unstemmed | GO-2D: identifying 2-dimensional cellular-localized functional modules in Gene Ontology |
title_short | GO-2D: identifying 2-dimensional cellular-localized functional modules in Gene Ontology |
title_sort | go-2d: identifying 2-dimensional cellular-localized functional modules in gene ontology |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1794235/ https://www.ncbi.nlm.nih.gov/pubmed/17250772 http://dx.doi.org/10.1186/1471-2164-8-30 |
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