BioRag - Bio Resource for Array Genes: An Online Resource for Analyzing and interpreting Microarray data

Ritu Pandey1, Raghavendra K Guru 2, David W Mount
1ritu@u.arizona.edu, Bioinformatics, Arizona Cancer Center, University of Arizona; 2graghave@cs.arizona.edu, Bioinformatics, Arizona Cancer Center, University of Arizona

Title:

BioRag (Bio Resource for Array Genes): An Online Resource for Analyzing and interpreting Microarray data

Author information:

Ritu Pandey, Raghavendra K Guru and David W Mount Bioinformatics Service, Arizona Cancer Center, University of Arizona, Tucson, AZ 85724, USA

One Page Abstract:

BioRag (Bio Resource for Array Genes) is a new platform designed as an online resource to assist researchers in analyzing results of microarray experiments and developing a biological interpretation of the results. This interactive tool allows users to selectively view a variety of information about gene function that is stored in resource database. Data for both human and mouse genes is dynamically collected and compiled twice a week from various public databases. Although there are other online resources that provide a similar comprehensive annotation and summary of genes, BioRag differs from these by further enabling researchers to mine biological relationships captured in the database using new query tools. BioRag can organize and cluster genes based on their interactions in biological pathways, their association with Gene Ontology terms, tissue/organ specific expression or any other user-chosen functional grouping of genes. A color coding scheme is used to highlight differential gene expression patterns against a background of gene functional information. Different tools offer different forms of display and visualization including a graphical representation of genes participating in a particular pathway or pathways and a bar graph representation of tissue-specific expression of each gene. BioRag uses the concept hierarchies (Anatomy and Diseases) of MESH (Medical Subject Heading) terms to organize the data related to tissue specific expression and diseases. This resource is currently being expanded to incorporate the publicly available protein-protein interaction data and new data mining tools. The data stored in BioRag can be accessed by other databases or software by linking to the URL given on the website using gene accession number. The ultimate objective of this database is to provide researchers and clinicians a unique and interactive platform for mining microarray data. Biorag is presently being used to interpret the unique gene expression patterns found in gastrointestinal and prostatic cancer tissues as biological changes that can lead to new diagnostic procedures and drug targets. The database is accessible at http://www.biorag.org.