Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction

O'Meara, M. J., Ballouz, S., Shoichet, B. K., Gillis, J. (2016) Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction. PLoS One, 11 (7). e0160098. ISSN 1932-6203 (Electronic)1932-6203 (Linking)

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DOI: 10.1371/journal.pone.0160098


The expansion of protein-ligand annotation databases has enabled large-scale networking of proteins by ligand similarity. These ligand-based protein networks, which implicitly predict the ability of neighboring proteins to bind related ligands, may complement biologically-oriented gene networks, which are used to predict functional or disease relevance. To quantify the degree to which such ligand-based protein associations might complement functional genomic associations, including sequence similarity, physical protein-protein interactions, co-expression, and disease gene annotations, we calculated a network based on the Similarity Ensemble Approach (SEA:, where protein neighbors reflect the similarity of their ligands. We also measured the similarity with functional genomic networks over a common set of 1,131 genes, and found that the networks had only small overlaps, which were significant only due to the large scale of the data. Consistent with the view that the networks contain different information, combining them substantially improved Molecular Function prediction within GO (from AUROC~0.63-0.75 for the individual data modalities to AUROC~0.8 in the aggregate). We investigated the boost in guilt-by-association gene function prediction when the networks are combined and describe underlying properties that can be further exploited.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > genomics and proteomics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function
bioinformatics > genomics and proteomics > Mapping and Rendering > ontology
CSHL Authors:
Communities: CSHL labs > Gillis Lab
Depositing User: Matt Covey
Date: 2016
Date Deposited: 04 Aug 2016 15:16
Last Modified: 07 Oct 2016 19:44
PMCID: PMC4965129
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