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Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization
BACKGROUND: In the last decade, a large amount of microarray gene expression data has been accumulated in public repositories. Integrating and analyzing high-throughput gene expression data have become key activities for exploring gene functions, gene networks and biological pathways. Effectively ut...
Autores principales: | , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2941691/ https://www.ncbi.nlm.nih.gov/pubmed/20727159 http://dx.doi.org/10.1186/1471-2105-11-433 |
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author | Zhang, Ming Zhang, Yudong Liu, Li Yu, Lijuan Tsang, Shirley Tan, Jing Yao, Wenhua Kang, Manjit S An, Yongqiang Fan, Xingming |
author_facet | Zhang, Ming Zhang, Yudong Liu, Li Yu, Lijuan Tsang, Shirley Tan, Jing Yao, Wenhua Kang, Manjit S An, Yongqiang Fan, Xingming |
author_sort | Zhang, Ming |
collection | PubMed |
description | BACKGROUND: In the last decade, a large amount of microarray gene expression data has been accumulated in public repositories. Integrating and analyzing high-throughput gene expression data have become key activities for exploring gene functions, gene networks and biological pathways. Effectively utilizing these invaluable microarray data remains challenging due to a lack of powerful tools to integrate large-scale gene-expression information across diverse experiments and to search and visualize a large number of gene-expression data points. RESULTS: Gene Expression Browser is a microarray data integration, management and processing system with web-based search and visualization functions. An innovative method has been developed to define a treatment over a control for every microarray experiment to standardize and make microarray data from different experiments homogeneous. In the browser, data are pre-processed offline and the resulting data points are visualized online with a 2-layer dynamic web display. Users can view all treatments over control that affect the expression of a selected gene via Gene View, and view all genes that change in a selected treatment over control via treatment over control View. Users can also check the changes of expression profiles of a set of either the treatments over control or genes via Slide View. In addition, the relationships between genes and treatments over control are computed according to gene expression ratio and are shown as co-responsive genes and co-regulation treatments over control. CONCLUSION: Gene Expression Browser is composed of a set of software tools, including a data extraction tool, a microarray data-management system, a data-annotation tool, a microarray data-processing pipeline, and a data search & visualization tool. The browser is deployed as a free public web service (http://www.ExpressionBrowser.com) that integrates 301 ATH1 gene microarray experiments from public data repositories (viz. the Gene Expression Omnibus repository at the National Center for Biotechnology Information and Nottingham Arabidopsis Stock Center). The set of Gene Expression Browser software tools can be easily applied to the large-scale expression data generated by other platforms and in other species. |
format | Text |
id | pubmed-2941691 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-29416912010-09-19 Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization Zhang, Ming Zhang, Yudong Liu, Li Yu, Lijuan Tsang, Shirley Tan, Jing Yao, Wenhua Kang, Manjit S An, Yongqiang Fan, Xingming BMC Bioinformatics Software BACKGROUND: In the last decade, a large amount of microarray gene expression data has been accumulated in public repositories. Integrating and analyzing high-throughput gene expression data have become key activities for exploring gene functions, gene networks and biological pathways. Effectively utilizing these invaluable microarray data remains challenging due to a lack of powerful tools to integrate large-scale gene-expression information across diverse experiments and to search and visualize a large number of gene-expression data points. RESULTS: Gene Expression Browser is a microarray data integration, management and processing system with web-based search and visualization functions. An innovative method has been developed to define a treatment over a control for every microarray experiment to standardize and make microarray data from different experiments homogeneous. In the browser, data are pre-processed offline and the resulting data points are visualized online with a 2-layer dynamic web display. Users can view all treatments over control that affect the expression of a selected gene via Gene View, and view all genes that change in a selected treatment over control via treatment over control View. Users can also check the changes of expression profiles of a set of either the treatments over control or genes via Slide View. In addition, the relationships between genes and treatments over control are computed according to gene expression ratio and are shown as co-responsive genes and co-regulation treatments over control. CONCLUSION: Gene Expression Browser is composed of a set of software tools, including a data extraction tool, a microarray data-management system, a data-annotation tool, a microarray data-processing pipeline, and a data search & visualization tool. The browser is deployed as a free public web service (http://www.ExpressionBrowser.com) that integrates 301 ATH1 gene microarray experiments from public data repositories (viz. the Gene Expression Omnibus repository at the National Center for Biotechnology Information and Nottingham Arabidopsis Stock Center). The set of Gene Expression Browser software tools can be easily applied to the large-scale expression data generated by other platforms and in other species. BioMed Central 2010-08-20 /pmc/articles/PMC2941691/ /pubmed/20727159 http://dx.doi.org/10.1186/1471-2105-11-433 Text en Copyright ©2010 Zhang 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 Zhang, Ming Zhang, Yudong Liu, Li Yu, Lijuan Tsang, Shirley Tan, Jing Yao, Wenhua Kang, Manjit S An, Yongqiang Fan, Xingming Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization |
title | Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization |
title_full | Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization |
title_fullStr | Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization |
title_full_unstemmed | Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization |
title_short | Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization |
title_sort | gene expression browser: large-scale and cross-experiment microarray data integration, management, search & visualization |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2941691/ https://www.ncbi.nlm.nih.gov/pubmed/20727159 http://dx.doi.org/10.1186/1471-2105-11-433 |
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