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MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters

BACKGROUND: Microarray technology makes it possible to identify changes in gene expression of an organism, under various conditions. Data mining is thus essential for deducing significant biological information such as the identification of new biological mechanisms or putative drug targets. While m...

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Detalles Bibliográficos
Autores principales: Law, Philip J, Claudel-Renard, Clotilde, Joubert, Fourie, Louw, Abraham I, Berger, Dave K
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2277412/
https://www.ncbi.nlm.nih.gov/pubmed/18307768
http://dx.doi.org/10.1186/1471-2164-9-105
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author Law, Philip J
Claudel-Renard, Clotilde
Joubert, Fourie
Louw, Abraham I
Berger, Dave K
author_facet Law, Philip J
Claudel-Renard, Clotilde
Joubert, Fourie
Louw, Abraham I
Berger, Dave K
author_sort Law, Philip J
collection PubMed
description BACKGROUND: Microarray technology makes it possible to identify changes in gene expression of an organism, under various conditions. Data mining is thus essential for deducing significant biological information such as the identification of new biological mechanisms or putative drug targets. While many algorithms and software have been developed for analysing gene expression, the extraction of relevant information from experimental data is still a substantial challenge, requiring significant time and skill. DESCRIPTION: MADIBA (MicroArray Data Interface for Biological Annotation) facilitates the assignment of biological meaning to gene expression clusters by automating the post-processing stage. A relational database has been designed to store the data from gene to pathway for Plasmodium, rice and Arabidopsis. Tools within the web interface allow rapid analyses for the identification of the Gene Ontology terms relevant to each cluster; visualising the metabolic pathways where the genes are implicated, their genomic localisations, putative common transcriptional regulatory elements in the upstream sequences, and an analysis specific to the organism being studied. CONCLUSION: MADIBA is an integrated, online tool that will assist researchers in interpreting their results and understand the meaning of the co-expression of a cluster of genes. Functionality of MADIBA was validated by analysing a number of gene clusters from several published experiments – expression profiling of the Plasmodium life cycle, and salt stress treatments of Arabidopsis and rice. In most of the cases, the same conclusions found by the authors were quickly and easily obtained after analysing the gene clusters with MADIBA.
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spelling pubmed-22774122008-04-01 MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters Law, Philip J Claudel-Renard, Clotilde Joubert, Fourie Louw, Abraham I Berger, Dave K BMC Genomics Database BACKGROUND: Microarray technology makes it possible to identify changes in gene expression of an organism, under various conditions. Data mining is thus essential for deducing significant biological information such as the identification of new biological mechanisms or putative drug targets. While many algorithms and software have been developed for analysing gene expression, the extraction of relevant information from experimental data is still a substantial challenge, requiring significant time and skill. DESCRIPTION: MADIBA (MicroArray Data Interface for Biological Annotation) facilitates the assignment of biological meaning to gene expression clusters by automating the post-processing stage. A relational database has been designed to store the data from gene to pathway for Plasmodium, rice and Arabidopsis. Tools within the web interface allow rapid analyses for the identification of the Gene Ontology terms relevant to each cluster; visualising the metabolic pathways where the genes are implicated, their genomic localisations, putative common transcriptional regulatory elements in the upstream sequences, and an analysis specific to the organism being studied. CONCLUSION: MADIBA is an integrated, online tool that will assist researchers in interpreting their results and understand the meaning of the co-expression of a cluster of genes. Functionality of MADIBA was validated by analysing a number of gene clusters from several published experiments – expression profiling of the Plasmodium life cycle, and salt stress treatments of Arabidopsis and rice. In most of the cases, the same conclusions found by the authors were quickly and easily obtained after analysing the gene clusters with MADIBA. BioMed Central 2008-02-28 /pmc/articles/PMC2277412/ /pubmed/18307768 http://dx.doi.org/10.1186/1471-2164-9-105 Text en Copyright © 2008 Law 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
Law, Philip J
Claudel-Renard, Clotilde
Joubert, Fourie
Louw, Abraham I
Berger, Dave K
MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters
title MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters
title_full MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters
title_fullStr MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters
title_full_unstemmed MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters
title_short MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters
title_sort madiba: a web server toolkit for biological interpretation of plasmodium and plant gene clusters
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2277412/
https://www.ncbi.nlm.nih.gov/pubmed/18307768
http://dx.doi.org/10.1186/1471-2164-9-105
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