Mendeley | Further Information

{"title"=>"Ligand similarity complements sequence, physical interaction, and Co-Expression for gene function prediction", "type"=>"journal", "authors"=>[{"first_name"=>"Matthew J.", "last_name"=>"O'Meara", "scopus_author_id"=>"55601810500"}, {"first_name"=>"Sara", "last_name"=>"Ballouz", "scopus_author_id"=>"26031942500"}, {"first_name"=>"Brian K.", "last_name"=>"Shoichet", "scopus_author_id"=>"7006416338"}, {"first_name"=>"Jesse Gillis", "last_name"=>"Gillis", "scopus_author_id"=>"35578536500"}], "year"=>2016, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84982688502", "pui"=>"611503298", "scopus"=>"2-s2.0-84982688502", "doi"=>"10.1371/journal.pone.0160098", "issn"=>"19326203"}, "id"=>"bd49b39f-c639-351f-bbee-c482a9d3d976", "abstract"=>"© 2016 O'Meara et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.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: sea.docking.org), 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 AUROCõ0.63-0.75 for the individual data modalities to AUROCõ0.8 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.", "link"=>"http://www.mendeley.com/research/ligand-similarity-complements-sequence-physical-interaction-coexpression-gene-function-prediction", "reader_count"=>10, "reader_count_by_academic_status"=>{"Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>1, "Student > Postgraduate"=>2, "Student > Master"=>1, "Student > Bachelor"=>1, "Lecturer"=>1, "Professor"=>1, "Unspecified"=>1}, "reader_count_by_user_role"=>{"Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>1, "Student > Postgraduate"=>2, "Student > Master"=>1, "Student > Bachelor"=>1, "Lecturer"=>1, "Professor"=>1, "Unspecified"=>1}, "reader_count_by_subject_area"=>{"Biochemistry, Genetics and Molecular Biology"=>5, "Medicine and Dentistry"=>1, "Agricultural and Biological Sciences"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>2, "Unspecified"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>5}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>2}, "Unspecified"=>{"Unspecified"=>1}}, "reader_count_by_country"=>{"Hungary"=>1}, "group_count"=>0}

CrossRef

• http://doi.org/10.1093/bioinformatics/bty593
• http://doi.org/10.1021/acs.jmedchem.7b01113
• http://doi.org/10.1128/mSphere.01245-20
• http://doi.org/10.1093/bioinformatics/bty287
• http://doi.org/10.1089/cmb.2019.0120

Scopus | Further Information

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F1000Prime