EPIC-DB: a proteomics database for studying Apicomplexan organisms.
BACKGROUND
High throughput proteomics experiments are useful for analyzing the protein expression of an organism, identifying the correct gene structure of a genome, or locating possible post-translational modifications within proteins. High throughput methods necessitate publicly accessible and easily queried databases for efficiently and logically storing, displaying, and analyzing the large volume of data.


METHODS
EPICDB is a publicly accessible, queryable, relational database that organizes and displays experimental, high throughput proteomics data for Toxoplasma gondii and Cryptosporidium parvum. Along with detailed information on mass spectrometry experiments, the database also provides antibody experimental results and analysis of functional annotations, comparative genomics, and aligned expressed sequence tag (EST) and genomic open reading frame (ORF) sequences. The database contains all available alternative gene datasets for each organism, which comprises a complete theoretical proteome for the respective organism, and all data is referenced to these sequences. The database is structured around clusters of protein sequences, which allows for the evaluation of redundancy, protein prediction discrepancies, and possible splice variants. The database can be expanded to include genomes of other organisms for which proteome-wide experimental data are available.


CONCLUSIONS
EPICDB is a comprehensive database of genome-wide T. gondii and C. parvum proteomics data and incorporates many features that allow for the analysis of the entire proteomes and/or annotation of specific protein sequences. EPICDB is complementary to other -genomics- databases of these organisms by offering complete mass spectrometry analysis on a comprehensive set of all available protein sequences.
Madrid-Aliste
Carlos J
CJ
Biodefense Proteomics Research Center, Albert Einstein College of Medicine, Bronx, NY 10461, USA. cmadrid@fiserlab.org
Dybas
Joseph M
JM
Angeletti
Ruth Hogue
RH
Weiss
Louis M
LM
Kim
Kami
K
Simon
Istvan
I
Fiser
Andras
A
D000818:Animals; D016785:Cryptosporidium parvum / Q000235:genetics*; D003628:Database Management Systems; D030562:Databases, Protein; D020224:Expressed Sequence Tags; D018503:Genome, Protozoan; D016366:Open Reading Frames; D020543:Proteome / Q000235:genetics; D040901:Proteomics; D014122:Toxoplasma / Q000235:genetics*; D014584:User-Computer Interface
D020543:Proteome