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GEDI: a user-friendly toolbox for analysis of large-scale gene expression data
BACKGROUND: Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experienc...
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/PMC2194737/ https://www.ncbi.nlm.nih.gov/pubmed/18021455 http://dx.doi.org/10.1186/1471-2105-8-457 |
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author | Fujita, André Sato, João R Ferreira, Carlos E Sogayar, Mari C |
author_facet | Fujita, André Sato, João R Ferreira, Carlos E Sogayar, Mari C |
author_sort | Fujita, André |
collection | PubMed |
description | BACKGROUND: Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills. RESULTS: Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al. CONCLUSION: GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology. |
format | Text |
id | pubmed-2194737 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-21947372008-01-12 GEDI: a user-friendly toolbox for analysis of large-scale gene expression data Fujita, André Sato, João R Ferreira, Carlos E Sogayar, Mari C BMC Bioinformatics Software BACKGROUND: Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills. RESULTS: Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al. CONCLUSION: GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology. BioMed Central 2007-11-19 /pmc/articles/PMC2194737/ /pubmed/18021455 http://dx.doi.org/10.1186/1471-2105-8-457 Text en Copyright © 2007 Fujita 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 Fujita, André Sato, João R Ferreira, Carlos E Sogayar, Mari C GEDI: a user-friendly toolbox for analysis of large-scale gene expression data |
title | GEDI: a user-friendly toolbox for analysis of large-scale gene expression data |
title_full | GEDI: a user-friendly toolbox for analysis of large-scale gene expression data |
title_fullStr | GEDI: a user-friendly toolbox for analysis of large-scale gene expression data |
title_full_unstemmed | GEDI: a user-friendly toolbox for analysis of large-scale gene expression data |
title_short | GEDI: a user-friendly toolbox for analysis of large-scale gene expression data |
title_sort | gedi: a user-friendly toolbox for analysis of large-scale gene expression data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2194737/ https://www.ncbi.nlm.nih.gov/pubmed/18021455 http://dx.doi.org/10.1186/1471-2105-8-457 |
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