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Nucleic Acids Research, 2004, Vol. 32, Database issue D326-D328
© 2004 Oxford University Press

ApiEST-DB: analyzing clustered EST data of the apicomplexan parasites

Li Li, Jonathan Crabtree1, Steve Fischer1, Deborah Pinney1, Christian J. Stoeckert, Jr1, L. David Sibley2 and David S. Roos*

Department of Biology and 1 Center for Bioinformatics, University of Pennsylvania, Philadelphia, PA 19104, USA and 2 Department of Molecular Microbiology, Washington University School of Medicine, St Louis, MO 63108, USA

*To whom correspondence should be addressed. Tel: +1 215 898 2118; Fax: +1 215 898 8780; Email: droos{at}sas.upenn.edu

ApiEST-DB (http://www.cbil.upenn.edu/paradbs-servlet/) provides integrated access to publicly available EST data from protozoan parasites in the phylum Apicomplexa. The database currently incorporates a total of nearly 100 000 ESTs from several parasite species of clinical and/or veterinary interest, including Eimeria tenella, Neospora caninum, Plasmodium falciparum, Sarcocystis neurona and Toxoplasma gondii. To facilitate analysis of these data, EST sequences were clustered and assembled to form consensus sequences for each organism, and these assemblies were then subjected to automated annotation via similarity searches against protein and domain databases. The underlying relational database infrastructure, Genomics Unified Schema (GUS), enables complex biologically based queries, facilitating validation of gene models, identification of alternative splicing, detection of single nucleotide polymorphisms, identification of stage-specific genes and recognition of phylogenetically conserved and phylogenetically restricted sequences.


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