Discovering and Mining Links for Protein Databases
Keywords:
Link analysis, Markov chain, correspondence analysis, graph mining, principal component analysisAbstract
This work introduces a link analysis procedure for discovering relationships in a protein database or a relational database generalizing simple correspondence analysis. It is based on extracting the links to the related protein database and malfunctioned protein database. The datasets are trained in order to find out missing interactions and the sequences related to them. Further the analysis of links proceeds by performing a random walk defining a Markov chain. The elements of interest are analysed through stochastic complementation which gives a reduced Markov chain. This reduced map is then analysed by projecting the elements of interest through Principal component analysis. Several Protein datasets are analysed using the proposed methodology, showing the usefulness of the technique for extracting relationships in relational databases or graphs.
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