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The NFI-Regulome Database: A tool for annotation and analysis of control regions of genes regulated by Nuclear Factor I transcription factors

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Author(s): Gronostajski Richard M | Guaneri Joseph | Lee Dong | Gallo Steven M

Journal: Journal of Clinical Bioinformatics
ISSN 2043-9113

Volume: 1;
Issue: 1;
Start page: 4;
Date: 2011;
Original page

ABSTRACT
Abstract Background Genome annotation plays an essential role in the interpretation and use of genome sequence information. While great strides have been made in the annotation of coding regions of genes, less success has been achieved in the annotation of the regulatory regions of genes, including promoters, enhancers/silencers, and other regulatory elements. One reason for this disparity in annotated information is that coding regions can be assessed using high-throughput techniques such as EST sequencing, while annotation of regulatory regions often requires a gene-by-gene approach. Results The NFI-Regulome database http://nfiregulome.ccr.buffalo.edu was designed to promote easy annotation of the regulatory regions of genes that contain binding sites for the NFI (Nuclear Factor I) family of transcription factors, using data from the published literature. Binding sites are annotated together with the sequence of the gene, obtained from the UCSC Genome site, and the locations of all binding sites for multiple genes can be displayed in a number of formats designed to facilitate inter-gene comparisons. Classes of genes based on expression pattern, disease involvement, or types of binding sites present can be readily compared in order to assess common "architectural" structures in the regulatory regions. Conclusions The NFI-Regulome database allows rapid display of the relative locations and number of transcription factor binding sites of individual or defined sets of genes that contain binding sites for NFI transcription factors. This database may in the future be expanded into a distributed database structure including other families of transcription factors. Such databases may be useful for identifying common regulatory structures in genes essential for organ development, tissue-specific gene expression or those genes related to specific diseases.
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