Article

Word and sentence embedding tools to measure semantic similarity of Gene Ontology terms by their definitions

2017-01-28

Abstract excerpt

The Gene Ontology (GO) database contains GO terms that describe biological functions of genes. Previous methods for comparing GO terms have relied on the fact that GO terms are organized into a tree structure. Under this paradigm, the locations of two GO terms in the tree dictate their similarity score. In this paper, we introduce two new solutions for this problem, by focusing instead on the definitions of the GO...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 76718a00-679e-5dca-8074-a25c74f4a08e
DOI: 10.1101/103648

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Word and sentence embedding tools to measure semantic similarity of Gene Ontology terms by their definitionsDOI 10.1101/103648Read

Text mining-based word representations for biomedical data analysis and machine learning tasksSemantic proximity Read

Uncovering the domain language of protein function and protein networks using DANSySemantic proximity Read

Gene2Vec: Distributed Representation of Genes Based on Co-ExpressionSemantic proximity Read

Supervised Semantic SimilaritySemantic proximity Read

Phenotype Extraction Based on Word Embedding to Sentence Embedding Cascaded Approach.Semantic proximity Read

Joint embedding of biological networks for cross-species functional alignmentSemantic proximity Read

Mimvec: a deep learning approach for analyzing the human phenome.Semantic proximity Read

Evaluating Sequence and Structural Similarity Metrics for Predicting Shared Paralog FunctionsSemantic proximity Read

Self-normalizing learning on biomedical ontologies using a deep Siamese neural networkSemantic proximity Read

Deep learning architectures for recognizing ontology concepts from scientific literatureSemantic proximity Read

Injecting domain knowledge into graph neural networks for protein-protein interactionsSemantic proximity Read

PhenoRerank: A re-ranking model for phenotypic concept recognition pre-trained on human phenotype ontology.Semantic proximity Read