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Nucleic Acids Research, 2003, Vol. 31, No. 1 390-392
© 2003 Oxford University Press

iProClass: an integrated database of protein family, function and structure information

Hongzhan Huang, Winona C. Barker1, Yongxing Chen1 and Cathy H. Wu*

Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, 3900 Reservoir Road, NW, Box 571414, Washington, DC 20057-1414, USA 1 National Biomedical Research Foundation, Georgetown University Medical Center, 3900 Reservoir Road, NW, Box 571414, Washington, DC 20057-1414, USA

*To whom correspondence should be addressed. Tel: +1 2026872121; Fax: +1 2026871662; Email: wuc{at}georgetown.edu

ABSTRACT

The iProClass database provides comprehensive, value-added descriptions of proteins and serves as a framework for data integration in a distributed networking environment. The protein information in iProClass includes family relationships as well as structural and functional classifications and features. The current version consists of about 830 000 non-redundant PIR-PSD, SWISS-PROT, and TrEMBL proteins organized with more than 36 000 PIR superfamilies, 145 000 families, 4000 domains, 1300 motifs and 550 000 FASTA similarity clusters. It provides rich links to over 50 database of protein sequences, families, functions and pathways, protein–protein interactions, post-translational modifications, protein expressions, structures and structural classifications, genes and genomes, ontologies, literature and taxonomy. Protein and superfamily summary reports present extensive annotation information and include membership statistics and graphical display of domains and motifs. iProClass employs an open and modular architecture for interoperability and scalability. It is implemented in the Oracle object-relational database system and is updated biweekly. The database is freely accessible from the web site at http://pir.georgetown.edu/iproclass/ and searchable by sequence or text string. The data integration in iProClass supports exploration of protein relationships. Such knowledge is fundamental to the understanding of protein evolution, structure and function and crucial to functional genomic and proteomic research.


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