G2D: a tool for mining genes associated with disease. BMC Genet 6:45

Ontario Genomics Innovation Centre, Ottawa Health Research Institute, ON K1H 8L6, Ottawa, Canada.
BMC Genetics (Impact Factor: 2.4). 02/2005; 6(1):45. DOI: 10.1186/1471-2156-6-45
Source: PubMed


Human inherited diseases can be associated by genetic linkage with one or more genomic regions. The availability of the complete sequence of the human genome allows examining those locations for an associated gene. We previously developed an algorithm to prioritize genes on a chromosomal region according to their possible relation to an inherited disease using a combination of data mining on biomedical databases and gene sequence analysis.
We have implemented this method as a web application in our site G2D (Genes to Diseases). It allows users to inspect any region of the human genome to find candidate genes related to a genetic disease of their interest. In addition, the G2D server includes pre-computed analyses of candidate genes for 552 linked monogenic diseases without an associated gene, and the analysis of 18 asthma loci.
G2D can be publicly accessed at

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Available from: Miguel Andrade
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    • "Recent studies showed that related phenotypes share common genetic basis and susceptibility genes [8] [9] [10] because the proteins involved in the pathogenesis are likely to interact together [11] [12] in a few biological pathways. Although there are previous studies on prioritizing disease-related genes by use of biological information [13] [14] [15] [16] [17] [18] [19] [20], using various kinds of biological information of human genes would be useful. Therefore, we developed a method to prioritize candidate genes for common diseases by utilizing biological information of human genes. "
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    • "Specifically, each reporter-level identifier (GenBank accession numbers) was mapped to a UniGene identifier (UniGene Cluster ID) [36-40]. The mapping was performed through the web-based tool SOURCE [41] in the 19th of November 2010, simultaneously for both platforms, in order to avoid inconsistencies [42]. All mapped reporter-level identifiers had one-to-one relationship with the gene-level identifiers that is, each reporter was associated with a single UniGene identifier and no more than one reporter was mapped to the same UniGene identifier. "
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    ABSTRACT: It has been shown previously that glucocorticoids exert a dual mechanism of action, entailing cytotoxic, mitogenic as well as cell proliferative and anti-apoptotic responses, in a dose-dependent manner on CCRF-CEM cells at 72 h. Early gene expression response implies a dose-dependent dual mechanism of action of prednisolone too, something reflected on cell state upon 72 h of treatment. In this work, a generic, computational microarray data analysis framework is proposed, in order to examine the hypothesis, whether CCRF-CEM cells exhibit an intrinsic or acquired mechanism of resistance and investigate the molecular imprint of this, upon prednisolone treatment. The experimental design enables the examination of both the dose (0 nM, 10 nM, 22 uM, 700 uM) effect of glucocorticoid exposure and the dynamics (early and late, namely 4 h, 72 h) of the molecular response of the cells at the transcriptomic layer. In this work, we demonstrated that CCRF-CEM cells may attain a mixed mechanism of response to glucocorticoids, however, with a clear preference towards an intrinsic mechanism of resistance. Specifically, at 4 h, prednisolone appeared to down-regulate apoptotic genes. Also, low and high prednisolone concentrations up-regulates genes related to metabolism and signal-transduction in both time points, thus favoring cell proliferative actions. In addition, regulation of NF-κB-related genes implies an inherent mechanism of resistance through the established link of NF-κB inflammatory role and GC-induced resistance. The analysis framework applied here highlights prednisolone-activated regulatory mechanisms through identification of early responding sets of genes. On the other hand, study of the prolonged exposure to glucocorticoids (72 h exposure) highlights the effect of homeostatic feedback mechanisms of the treated cells. Overall, it appears that CCRF-CEM cells in this study exhibit a diversified, combined pattern of intrinsic and acquired resistance to prednisolone, with a tendency towards inherent resistant characteristics, through activation of different molecular courses of action.
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    • "ENDEAVOUR is trained on genes involved in a known biological process and ranks candidate genes after considering several genomic data sources (Tranchevent et al., 2008). G2D prioritization strategy is based on a combination of data mining on biomedical databases and sequence features (Perez-Iratxeta et al., 2005). PolySearch analyzes biomedical databases to build relationships between diseases, genes, mutations, drugs, pathways, tissues, organs and metabolites in humans (Cheng et al., 2008). "
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