RT Journal Article
SR Electronic
T1 Supervised Semantic Similarity
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.02.16.431402
DO 10.1101/2021.02.16.431402
A1 Rita T. Sousa
A1 Sara Silva
A1 Catia Pesquita
YR 2021
UL http://biorxiv.org/content/early/2021/05/11/2021.02.16.431402.abstract
AB Background Semantic similarity between concepts in knowledge graphs is essential for several bioinformatics applications, including the prediction of protein-protein interactions and the discovery of associations between diseases and genes. Although knowledge graphs describe entities in terms of several perspectives (or semantic aspects), state-of-the-art semantic similarity measures are general-purpose. This can represent a challenge since different use cases for the application of semantic similarity may need different similarity perspectives and ultimately depend on expert knowledge for manual fine-tuning.Results We present a new approach that uses supervised machine learning to tailor aspect-oriented semantic similarity measures to fit a particular view on biological similarity or relatedness. We implement and evaluate it using different combinations of representative semantic similarity measures and machine learning methods with four biological similarity views: protein-protein interaction, protein function similarity, protein sequence similarity and phenotype-based gene similarity.Conclusions The results demonstrate that our approach outperforms non-supervised methods, producing semantic similarity models that fit different biological perspectives significantly better than the commonly used manual combinations of semantic aspects.Competing Interest StatementThe authors have declared no competing interest.AbbreviationsBPBiological ProcessBRBayesian RidgeCCCellular ComponentDTDecision TreeGOGene OntologyGPGenetic ProgrammingHPHuman Phenotype OntologyKGKnowledge GraphICInformation ContentQRInterquartile RangeKNNK-Nearest NeighborLRLinearRegressionMFMolecular FunctionMLMachine LearningMLPMulti-Layer PerceptionPPIProtein-Protein InteractionRFRandom ForestSSMSemantic Similarity MeasureXGBXGBoost.