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Published in 2017 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btx275
Abstract: Motivation : Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are…
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Keywords:
knowledge;
knowledge graphs;
learning biological;
biological knowledge ... See more keywords
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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…
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Keywords:
knowledge;
biokeen library;
knowledge graph;
graph embeddings ... See more keywords
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Published in 2022 at "Computational Linguistics"
DOI: 10.1162/coli_a_00462
Abstract: Abstract Specialized transformers-based models (such as BioBERT and BioMegatron) are adapted for the biomedical domain based on publicly available biomedical corpora. As such, they have the potential to encode large-scale biological knowledge. We investigate the…
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Keywords:
background knowledge;
biomedical background;
representation biomedical;
knowledge ... See more keywords
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Published in 2018 at "F1000Research"
DOI: 10.12688/f1000research.16605.1
Abstract: KnetMaps is a BioJS component for the interactive visualization of biological knowledge networks. It is well suited for applications that need to visualise complementary, connected and content-rich data in a single view in order to…
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Keywords:
knowledge;
component visualize;
knowledge networks;
knetmaps biojs ... See more keywords