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   Articles with "graph embeddings" as a keyword



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Effective Knowledge Graph Embeddings based on Multidirectional Semantics Relations for Polypharmacy Side Effects Prediction.

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recommendations! Published in 2022 at "Bioinformatics"

DOI: 10.1093/bioinformatics/btac094

Abstract: MOTIVATION Polypharmacy is the combined use of drugs for the treatment of diseases. However, it often shows a high risk of side effects. Due to unnecessary interactions of combined drugs, the side effects of polypharmacy… read more here.

Keywords: semantics; multidirectional semantics; graph embeddings; side effects ... See more keywords
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BioKEEN: a library for learning and evaluating biological knowledge graph embeddings

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recommendations! Published in 2019 at "Bioinformatics"

DOI: 10.1093/bioinformatics/btz117

Abstract: SUMMARY Knowledge graph embeddings (KGEs) have received significant attention in other domains due to their ability to predict links and create dense representations for graphs' nodes and edges. However, the software ecosystem for their application… read more here.

Keywords: knowledge; biokeen library; knowledge graph; graph embeddings ... See more keywords
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Metagenomic binning with assembly graph embeddings

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recommendations! Published in 2022 at "Bioinformatics"

DOI: 10.1101/2022.02.25.481923

Abstract: Despite recent advancements in sequencing technologies and assembly methods, obtaining high-quality microbial genomes from metagenomic samples is still not a trivial task. Current metagenomic binners do not take full advantage of assembly graphs and are… read more here.

Keywords: graph; assembly graph; graph embeddings; binning assembly ... See more keywords
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GO2Vec: transforming GO terms and proteins to vector representations via graph embeddings

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recommendations! Published in 2019 at "BMC Genomics"

DOI: 10.1186/s12864-019-6272-2

Abstract: Semantic similarity between Gene Ontology (GO) terms is a fundamental measure for many bioinformatics applications, such as determining functional similarity between genes or proteins. Most previous research exploited information content to estimate the semantic similarity… read more here.

Keywords: terms proteins; information; similarity; vector representations ... See more keywords