Database Commons

a catalog of worldwide biological databases

iRefWeb is a resource that provides web interface to a large collection of protein-protein interactions aggregated from major primary databases. The underlying data-consolidation process, called iRefIndex, implements a rigorous methodology of identifying redundant protein sequences and integrating disparate data records that reference the same peptide sequences, despite many potential differences in data identifiers across various source databases. iRefWeb offers a unified user interface to all interaction records and associated information collected by iRefIndex, in addition to a number of data filters and visual features that present the supporting evidence. Users of iRefWeb can explore the consolidated landscape of protein-protein interactions, establish the provenance and reliability of each data record, and compare annotations performed by different data curator teams. The iRefWeb portal is freely available at http://wodaklab.org/iRefWeb .

Literature curation of protein interaction data faces a number of challenges. Although curators increasingly adhere to standard data representations, the data that various databases actually record from the same published information may differ significantly. Some of the reasons underlying these differences are well known, but their global impact on the interactions collectively curated by major public databases has not been evaluated. Here we quantify the agreement between curated interactions from 15?471 publications shared across nine major public databases. Results show that on average, two databases fully agree on 42% of the interactions and 62% of the proteins curated from the same publication. Furthermore, a sizable fraction of the measured differences can be attributed to divergent assignments of organism or splice isoforms, different organism focus and alternative representations of multi-protein complexes. Our findings highlight the impact of divergent curation policies across databases, and should be relevant to both curators and data consumers interested in analyzing protein-interaction data generated by the scientific community. Database URL: http://wodaklab.org/iRefWeb.

There is no biological or epidemiological data on the association between NOS3 promoter polymorphisms and prostate cancer. The polymorphisms in the promoter region of NOS3 gene may be responsible for variations in the plasma NO, which may promote cancer progression by providing a selective growth advantage to tumor cells by angiogenic stimulus and by direct DNA damage. This study aimed evaluating the NOS3 promoter polymorphisms by PCR-SSCP and sequencing, associating genotypes and haplotypes with NOS3 expression levels through semi-quantitative RT-PCR, and with PCA3 mRNA detection, a specific tumor biomarker, in the peripheral blood of pre-surgical samples from 177 patients; 83 PCa and 94 BPH. Three novel SNPs were identified -764A>G, -714G>T and -649G>A in the NOS3 gene promoter region, which together with the -786T>C generated four haplotypes (N, T, C, A). NOS3 gene expression levels were affected by the -786T>C polymorphism, and there was a 2-fold increase in NOS3 levels favored by the incorporation of each C allele. NOS3 levels higher than 80% of the constitutive gene expression level (B2M) presented a 4-fold increase in PCa occurrence. The -786T>C polymorphism was the most important promoter alteration of the NOS3 gene that may affect the PCa progression, but not its occurrence, and the incorporation of the C allele is associated with increased levels of NOS3 transcripts. The NOS3 transcript levels presented a bimodal behavior in tumor development and may be used as a biomarker together with the PCA3 marker for molecular staging of the prostate cancer.