Selected article for: "machine learning and protein pair"

Author: Kshirsagar, Meghana; Carbonell, Jaime; Klein-Seetharaman, Judith
Title: Multitask learning for host–pathogen protein interactions
  • Document date: 2013_7_1
  • ID: sdgt2ms5_9
    Snippet: In particular, supervised machine learning-based methods use the few experimentally discovered interactions as training data and formulate the interaction prediction problem in a classification setting, with target classes: 'interacting' or 'non-interacting'. Features are derived for each host-pathogen protein pair using various attributes of the two proteins such as protein sequence, gene expression, gene ontology (GO) etc. The general outline o.....
    Document: In particular, supervised machine learning-based methods use the few experimentally discovered interactions as training data and formulate the interaction prediction problem in a classification setting, with target classes: 'interacting' or 'non-interacting'. Features are derived for each host-pathogen protein pair using various attributes of the two proteins such as protein sequence, gene expression, gene ontology (GO) etc. The general outline of the supervised PPI prediction procedure is illustrated in Supplementary Figure S1 .

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