Database

AbMiner: A bioinformatic resource on available monoclonal antibodies and corresponding gene identifiers for genomic, proteomic, and immunologic studies

Sylvia M Major^1,4 , Satoshi Nishizuka^1,5,6 , Daisaku Morita^1,7 , Rick Rowland² , Margot Sunshine³ , Uma Shankavaram¹ , Frank Washburn^1,8 , Daniel Asin^1,9 , Hosein Kouros-Mehr^1,10 , David Kane³ and John N Weinstein¹

¹Genomics and Bioinformatics Group, Laboratory of Molecular Pharmacology, National Cancer Institute, National Institutes of Health, Bethesda, USA

²Center for Information Technology, National Institutes of Health, Bethesda, USA

³SRA International, 4300 Fair Lakes Court, Fairfax, USA

⁴University of California at Los Angeles, Department of Ecology and Evolutionary Biology, Los Angeles, USA

⁵Molecular Translational Technology, Molecular Therapeutics Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, USA

⁶Laboratory of Proteomics and Analytical Technologies, Research Technology Program, National Cancer Institute, SAIC-Frederick, Frederic, USA

⁷Department of Pathology II, National Defense Medical College, Namiki 3-2, Tokorozawa, Japan

⁸Harvard University, Cambridge, USA

⁹Washington University, St. Louis, USA

¹⁰Department of Anatomy, University of California, San Francisco, San Francisco,

author email corresponding author email

BMC Bioinformatics 2006, 7:192doi:10.1186/1471-2105-7-192

Published:	6 April 2006

Abstract

Background

Monoclonal antibodies are used extensively throughout the biomedical sciences for detection of antigens, either in vitro or in vivo. We, for example, have used them for quantitation of proteins on "reverse-phase" protein lysate arrays. For those studies, we quality-controlled > 600 available monoclonal antibodies and also needed to develop precise information on the genes that encode their antigens. Translation among the various protein and gene identifier types proved non-trivial because of one-to-many and many-to-one relationships. To organize the antibody, protein, and gene information, we initially developed a relational database in Filemaker for our own use. When it became apparent that the information would be useful to many other researchers faced with the need to choose or characterize antibodies, we developed it further as AbMiner, a fully relational web-based database under MySQL, programmed in Java.

Description

AbMiner is a user-friendly, web-based relational database of information on > 600 commercially available antibodies that we validated by Western blot for protein microarray studies. It includes many types of information on the antibody, the immunogen, the vendor, the antigen, and the antigen's gene. Multiple gene and protein identifier types provide links to corresponding entries in a variety of other public databases, including resources for phosphorylation-specific antibodies. AbMiner also includes our quality-control data against a pool of 60 diverse cancer cell types (the NCI-60) and also protein expression levels for the NCI-60 cells measured using our high-density "reverse-phase" protein lysate microarrays for a selection of the listed antibodies. Some other available database resources give information on antibody specificity for one or a couple of cell types. In contrast, the data in AbMiner indicate specificity with respect to the antigens in a pool of 60 diverse cell types from nine different tissues of origin.

Conclusion

AbMiner is a relational database that provides extensive information from our own laboratory and other sources on more than 600 available antibodies and the genes that encode the antibodies' antigens. The data will be made freely available at http://discover.nci.nih.gov/abminer webcite