A.C. Faria-Campos, R.R. Gomes, F.S. Moratelli, H. Rausch-Fernandes, G.R. Franco, S.V.A. Campos
Published October 05, 2007
Genet. Mol. Res. 6 (4): 937-945 (2007)
About the authors
A.C. Faria-Campos, R.R. Gomes, F.S. Moratelli, H. Rausch-Fernandes, G.R. Franco, S.V.A. Campos
Corresponding author
A.C. Faria-Campos
E-mail: alessa@icb.ufmg.br
ABSTRACT
Proteomics correspond to the identification and quantitative analysis of proteins expressed in different conditions or life stages of a cell or organism. Methods used in proteomics analysis include mainly chromatography, two-dimensional electrophoresis and mass spectrometry. Data generated in proteomics analysis vary significantly, and to identify a protein it is often necessary to perform a series of experiments, comparing its results to those found in proteomics databases. Existing proteomics databases are usually related to only one type of experiment or represent processed results, not raw data. Therefore, proteomics researchers frequently have to resort to several data repositories in order to be able to perform the identification. In this paper, we propose an integrated proteomics and transcriptomics database that stores raw and processed data, which are indexed allowing them to be retrieved together or individually. The proposed database, dubbed BNDb for Biomolecules Nucleus Database, is implemented using an MySQL server and is being used to store data from the parasite Schistosoma mansoni, the scorpion Tittyus serrulatus and the spider Phoneutria nigriventer. The database construction uses a relational approach and data indexes. The data model proposed uses groups of tables for each data subtype, which store details regarding the experimental procedure as well as raw data, analysis results and associated publications. BNDb also stores transcriptomics data publicly available which are associated with identifications performed on new samples. By using BNDb, we expect not only to contribute to proteomics research but also to provide a useful service for the scientific community.
Key words: Databases, Proteomics, Transcriptomics, Schistosoma, Data integration, MySQL