BACKGROUND: An important objective of DNA microarray-based gene expression experimentation is determining inter-relationships that exist between differentially expressed genes and biological processes, molecular functions, cellular components, signaling pathways, physiologic processes and diseases. RESULTS: Here we describe GeneMesh, a web-based program that facilitates analysis of DNA microarray gene expression data. GeneMesh relates genes in a query set to categories available in the Medical Subject Headings (MeSH) hierarchical index. The interface enables hypothesis driven relational analysis to a specific MeSH subcategory (e.g., Cardiovascular System, Genetic Processes, Immune System Diseases etc.) or unbiased relational analysis to broader MeSH categories (e.g., Anatomy, Biological Sciences, Disease etc.). Genes found associated with a given MeSH category are dynamically linked to facilitate tabular and graphical depiction of Entrez Gene information, Gene Ontology information, KEGG metabolic pathway diagrams and intermolecular interaction information. Expression intensity values of groups of genes that cluster in relation to a given MeSH category, gene ontology or pathway can be displayed as heat maps of Z score-normalized values. GeneMesh operates on gene expression data derived from a number of commercial microarray platforms including Affymetrix, Agilent and Illumina. CONCLUSIONS: GeneMesh is a versatile web-based tool for testing and developing new hypotheses through relating genes in a query set (e.g., differentially expressed genes from a DNA microarray experiment) to descriptors making up the hierarchical structure of the National Library of Medicine controlled vocabulary thesaurus, MeSH. The system further enhances the discovery process by providing links between sets of genes associated with a given MeSH category to a rich set of html linked tabular and graphic information including Entrez Gene summaries, gene ontologies, intermolecular interactions, overlays of genes onto KEGG pathway diagrams and heatmaps of expression intensity values. GeneMesh is freely available online at http://proteogenomics.musc.edu/genemesh/.

BACKGROUND: Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow these programs to be executed over the Internet enhances the applicability and utility of these analytic software tools. RESULTS: Here we present ArrayQuest, a web-based DNA microarray analysis process controller. Key features of ArrayQuest are that (1) it is capable of executing numerous analysis programs such as those written in R, BioPerl and C++; (2) new analysis programs can be added to ArrayQuest Methods Library at the request of users or developers; (3) input DNA microarray data can be selected from public databases (i.e., the Medical University of South Carolina (MUSC) DNA Microarray Database or Gene Expression Omnibus (GEO)) or it can be uploaded to the ArrayQuest center-point web server into a password-protected area; and (4) analysis jobs are distributed across computers configured in a backend cluster. To demonstrate the utility of ArrayQuest we have populated the methods library with methods for analysis of Affymetrix DNA microarray data. CONCLUSION: ArrayQuest enables browser-based implementation of DNA microarray data analysis programs that can be executed on a Linux-based platform. Importantly, ArrayQuest is a platform that will facilitate the distribution and implementation of new analysis algorithms and is therefore of use to both developers of analysis applications as well as users. ArrayQuest is freely available for use at http://proteogenomics.musc.edu/arrayquest.html.

SUMMARY: The Medical University of South Carolina (MUSC) DNA Microarray Database is a web-accessible archive of DNA microarray data. The database was developed using the DNA microarray project/data management system, micro ArrayDB. Annotations for each DNA microarray project and associated cRNA target information are stored in a MySQL relational database and linked to array hybridization data (raw and normalized). At the discretion of investigators, data are placed into the public domain where they can be interrogated and downloaded through a web browser. In addition to serving as an online resource of gene expression data, the MUSC DNA Microarray Database is a model for other academic DNA microarray data repositories. AVAILABILITY: Browsing and downloading of MUSC DNA Microarray Database information can be done after registration at http://proteogenomics.musc.edu/pss/home.php.