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PathEx: a novel multi factors based datasets selector web tool
BACKGROUND: Microarray experiments have become very popular in life science research. However, if such experiments are only considered independently, the possibilities for analysis and interpretation of many life science phenomena are reduced. The accumulation of publicly available data provides bio...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978222/ https://www.ncbi.nlm.nih.gov/pubmed/20969778 http://dx.doi.org/10.1186/1471-2105-11-528 |
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author | Bareke, Eric Pierre, Michael Gaigneaux, Anthoula Meulder, Bertrand De Depiereux, Sophie Habra, Naji Depiereux, Eric |
author_facet | Bareke, Eric Pierre, Michael Gaigneaux, Anthoula Meulder, Bertrand De Depiereux, Sophie Habra, Naji Depiereux, Eric |
author_sort | Bareke, Eric |
collection | PubMed |
description | BACKGROUND: Microarray experiments have become very popular in life science research. However, if such experiments are only considered independently, the possibilities for analysis and interpretation of many life science phenomena are reduced. The accumulation of publicly available data provides biomedical researchers with a valuable opportunity to either discover new phenomena or improve the interpretation and validation of other phenomena that partially understood or well known. This can only be achieved by intelligently exploiting this rich mine of information. DESCRIPTION: Considering that technologies like microarrays remain prohibitively expensive for researchers with limited means to order their own experimental chips, it would be beneficial to re-use previously published microarray data. For certain researchers interested in finding gene groups (requiring many replicates), there is a great need for tools to help them to select appropriate datasets for analysis. These tools may be effective, if and only if, they are able to re-use previously deposited experiments or to create new experiments not initially envisioned by the depositors. However, the generation of new experiments requires that all published microarray data be completely annotated, which is not currently the case. Thus, we propose the PathEx approach. CONCLUSION: This paper presents PathEx, a human-focused web solution built around a two-component system: one database component, enriched with relevant biological information (expression array, omics data, literature) from different sources, and another component comprising sophisticated web interfaces that allow users to perform complex dataset building queries on the contents integrated into the PathEx database. |
format | Text |
id | pubmed-2978222 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-29782222010-11-11 PathEx: a novel multi factors based datasets selector web tool Bareke, Eric Pierre, Michael Gaigneaux, Anthoula Meulder, Bertrand De Depiereux, Sophie Habra, Naji Depiereux, Eric BMC Bioinformatics Database BACKGROUND: Microarray experiments have become very popular in life science research. However, if such experiments are only considered independently, the possibilities for analysis and interpretation of many life science phenomena are reduced. The accumulation of publicly available data provides biomedical researchers with a valuable opportunity to either discover new phenomena or improve the interpretation and validation of other phenomena that partially understood or well known. This can only be achieved by intelligently exploiting this rich mine of information. DESCRIPTION: Considering that technologies like microarrays remain prohibitively expensive for researchers with limited means to order their own experimental chips, it would be beneficial to re-use previously published microarray data. For certain researchers interested in finding gene groups (requiring many replicates), there is a great need for tools to help them to select appropriate datasets for analysis. These tools may be effective, if and only if, they are able to re-use previously deposited experiments or to create new experiments not initially envisioned by the depositors. However, the generation of new experiments requires that all published microarray data be completely annotated, which is not currently the case. Thus, we propose the PathEx approach. CONCLUSION: This paper presents PathEx, a human-focused web solution built around a two-component system: one database component, enriched with relevant biological information (expression array, omics data, literature) from different sources, and another component comprising sophisticated web interfaces that allow users to perform complex dataset building queries on the contents integrated into the PathEx database. BioMed Central 2010-10-22 /pmc/articles/PMC2978222/ /pubmed/20969778 http://dx.doi.org/10.1186/1471-2105-11-528 Text en Copyright ©2010 Bareke 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 | Database Bareke, Eric Pierre, Michael Gaigneaux, Anthoula Meulder, Bertrand De Depiereux, Sophie Habra, Naji Depiereux, Eric PathEx: a novel multi factors based datasets selector web tool |
title | PathEx: a novel multi factors based datasets selector web tool |
title_full | PathEx: a novel multi factors based datasets selector web tool |
title_fullStr | PathEx: a novel multi factors based datasets selector web tool |
title_full_unstemmed | PathEx: a novel multi factors based datasets selector web tool |
title_short | PathEx: a novel multi factors based datasets selector web tool |
title_sort | pathex: a novel multi factors based datasets selector web tool |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978222/ https://www.ncbi.nlm.nih.gov/pubmed/20969778 http://dx.doi.org/10.1186/1471-2105-11-528 |
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