Blog
About

41
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          We present BioGraph, a data integration and data mining platform for the exploration and discovery of biomedical information. The platform offers prioritizations of putative disease genes, supported by functional hypotheses. We show that BioGraph can retrospectively confirm recently discovered disease genes and identify potential susceptibility genes, outperforming existing technologies, without requiring prior domain knowledge. Additionally, BioGraph allows for generic biomedical applications beyond gene discovery. BioGraph is accessible at http://www.biograph.be.

          Related collections

          Most cited references 47

          • Record: found
          • Abstract: not found
          • Article: not found

          Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            KEGG for linking genomes to life and the environment

            KEGG (http://www.genome.jp/kegg/) is a database of biological systems that integrates genomic, chemical and systemic functional information. KEGG provides a reference knowledge base for linking genomes to life through the process of PATHWAY mapping, which is to map, for example, a genomic or transcriptomic content of genes to KEGG reference pathways to infer systemic behaviors of the cell or the organism. In addition, KEGG provides a reference knowledge base for linking genomes to the environment, such as for the analysis of drug-target relationships, through the process of BRITE mapping. KEGG BRITE is an ontology database representing functional hierarchies of various biological objects, including molecules, cells, organisms, diseases and drugs, as well as relationships among them. KEGG PATHWAY is now supplemented with a new global map of metabolic pathways, which is essentially a combined map of about 120 existing pathway maps. In addition, smaller pathway modules are defined and stored in KEGG MODULE that also contains other functional units and complexes. The KEGG resource is being expanded to suit the needs for practical applications. KEGG DRUG contains all approved drugs in the US and Japan, and KEGG DISEASE is a new database linking disease genes, pathways, drugs and diagnostic markers.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              BioGRID: a general repository for interaction datasets

              Access to unified datasets of protein and genetic interactions is critical for interrogation of gene/protein function and analysis of global network properties. BioGRID is a freely accessible database of physical and genetic interactions available at . BioGRID release version 2.0 includes >116 000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens. Over 30 000 interactions have recently been added from 5778 sources through exhaustive curation of the Saccharomyces cerevisiae primary literature. An internally hyper-linked web interface allows for rapid search and retrieval of interaction data. Full or user-defined datasets are freely downloadable as tab-delimited text files and PSI-MI XML. Pre-computed graphical layouts of interactions are available in a variety of file formats. User-customized graphs with embedded protein, gene and interaction attributes can be constructed with a visualization system called Osprey that is dynamically linked to the BioGRID.
                Bookmark

                Author and article information

                Journal
                Genome Biol
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2011
                22 June 2011
                : 12
                : 6
                : R57
                Affiliations
                [1 ]Applied Molecular Genomics group, VIB Department of Molecular Genetics, Universiteit Antwerpen, Universiteitsplein 1, 2610 Wilrijk, Belgium
                [2 ]Advanced Database Research and Modelling group, Department of Mathematics and Computer Science, Universiteit Antwerpen, Groenenborgerlaan 171, 2020 Antwerpen, Belgium
                [3 ]Computational Linguistics and Psycholinguistics Research Center, Universiteit Antwerpen, Prinsstraat 13, 2000, Antwerpen, Belgium
                Article
                gb-2011-12-6-r57
                10.1186/gb-2011-12-6-r57
                3218845
                21696594
                Copyright ©2011 Liekens et al; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

                Categories
                Software

                Genetics

                Comments

                Comment on this article