- Title
- The Gene Interaction Miner: a new tool for data mining contextual information for protein-protein interaction analysis
- Creator
- Ikin, Aaron; Riveros, Carlos; Moscato, Pablo; Mendes, Alexandre
- Relation
- Bioinformatics Vol. 26, Issue 2, p. 283-284
- Publisher Link
- http://dx.doi.org/10.1093/bioinformatics/btp652
- Publisher
- Oxford University Press
- Resource Type
- journal article
- Date
- 2010
- Description
- Motivation: This work was motivated by the need for an automated tool for discovery of genetic networks and the availability of extensive contextual protein–protein interaction information in the iHOP repository. At the moment, this information cannot be explored to its full potential due to the lack of software tools to reliably collect, process and display that information in a way that life scientists can quickly analyze genes of interest and search for potential interaction networks. Commercial tools can perform a similar job, but results appear to be less informative than those obtained using contextual information. Results: The Gene Interaction Miner (GIM) could successfully uncover complex network structures of protein–protein interactions for a test dataset composed of genes already related to Alzheimer's disease. That same set, when examined using two other analysis tools, namely STRING and Pathway Studio, resulted in incomplete protein–protein interaction networks, which indicate that the use of curated databases only gives a partial picture of the biological processes behind the disease. Availability: The dataset used in this work and a running version of the software tool is available for download from the web site http://www.cs.newcastle.edu.au/∼mendes/softwareGIM.html.
- Subject
- Gene Interaction Miner (GIM); data mining; protein–protein interaction; gene analysis
- Identifier
- uon:9256
- Identifier
- http://hdl.handle.net/1959.13/921140
- Identifier
- ISSN:1367-4803
- Rights
- This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Bioinformatics following peer review. The definitive publisher-authenticated version Vol. 26, Issue 2, p. 283-284 is available online at: http://bioinformatics.oxfordjournals.org/content/26/2/283
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