Comparative analysis of microarray expression studies is difficult because of the great influence of technical factors on the experimental results. Yet, highlighted differentially expressed genes May allusion to the same biological processes.
However, Conservative manually transfer of genes to biological processes, as pursued by the Gene Ontology (GO) consortium, is incomplete and limited. We automatic assumption that the association of genes with biological processes through thesaurus-controlled mining Medline summaries would be more effective.
Hence, we developed a novel algorithm (LAMA: Literature-Aided meta-analysis) to quantify the similarity between transcriptomics studies. We evaluated our algorithm on a large collection of 102 microarray studies published in muscle development and disease and compared the similarity measures based on gene duplication and over-representation of biological processes assigned by GO.
Results: Although the overlap in the two genes and over-GO-which was poor, LAMA found much more biologically significant links between studies, with much weaker influence of technical factors. LAMA properly grouped muscular dystrophy, regeneration and myositis studies, and linked patient and studies mouse model.
LAMA also gets the connection of biological concepts. Among other new discoveries, we Cullin proteins associated ubiquitinylation a class of proteins, genes with a regulated during muscle regeneration, while ubiquitinylation has already been reported to be undertaken during the reverse process: muscular atrophy.
Conclusion: Our literature based on an analysis of association is able to find hidden biological common denominators in microarray studies, and circumvent the need for raw data analysis or Conservative genes annotation of databases.
Author: Rob Jelier, Peter AC 't Hoen, Ellen Sterrenburg, Johan T. den Dunnen, Gert-Jan van Ommen B., Jan A. Kors and Barend Mons
Credits / Source: BMC Bioinformatics 2008, 9:291
However, Conservative manually transfer of genes to biological processes, as pursued by the Gene Ontology (GO) consortium, is incomplete and limited. We automatic assumption that the association of genes with biological processes through thesaurus-controlled mining Medline summaries would be more effective.
Hence, we developed a novel algorithm (LAMA: Literature-Aided meta-analysis) to quantify the similarity between transcriptomics studies. We evaluated our algorithm on a large collection of 102 microarray studies published in muscle development and disease and compared the similarity measures based on gene duplication and over-representation of biological processes assigned by GO.
Results: Although the overlap in the two genes and over-GO-which was poor, LAMA found much more biologically significant links between studies, with much weaker influence of technical factors. LAMA properly grouped muscular dystrophy, regeneration and myositis studies, and linked patient and studies mouse model.
LAMA also gets the connection of biological concepts. Among other new discoveries, we Cullin proteins associated ubiquitinylation a class of proteins, genes with a regulated during muscle regeneration, while ubiquitinylation has already been reported to be undertaken during the reverse process: muscular atrophy.
Conclusion: Our literature based on an analysis of association is able to find hidden biological common denominators in microarray studies, and circumvent the need for raw data analysis or Conservative genes annotation of databases.
Author: Rob Jelier, Peter AC 't Hoen, Ellen Sterrenburg, Johan T. den Dunnen, Gert-Jan van Ommen B., Jan A. Kors and Barend Mons
Credits / Source: BMC Bioinformatics 2008, 9:291
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