BioKEEN: A library for learning and evaluating biological knowledge graph embeddings

Mehdi Ali; Charles Tapley Hoyt; Daniel Domingo-Fernández; Jens Lehmann; Hajira Jabeen

doi:10.1101/475202

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BioKEEN: A library for learning and evaluating biological knowledge graph embeddings

View ORCID ProfileMehdi Ali, View ORCID ProfileCharles Tapley Hoyt, View ORCID ProfileDaniel Domingo-Fernández, View ORCID ProfileJens Lehmann, Hajira Jabeen

doi: https://doi.org/10.1101/475202

Mehdi Ali

1Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn 53113, Germany

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Charles Tapley Hoyt

1Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn 53113, Germany

2Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin 53754, Germany

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Daniel Domingo-Fernández

1Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn 53113, Germany

2Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin 53754, Germany

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Jens Lehmann

1Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn 53113, Germany

3Department of Enterprise Information Systems, Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), Sankt Augustin 53754, Germany

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Hajira Jabeen

1Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn 53113, Germany

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Posted November 23, 2018.

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BioKEEN: A library for learning and evaluating biological knowledge graph embeddings

Mehdi Ali, Charles Tapley Hoyt, Daniel Domingo-Fernández, Jens Lehmann, Hajira Jabeen

bioRxiv 475202; doi: https://doi.org/10.1101/475202

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BioKEEN: A library for learning and evaluating biological knowledge graph embeddings

Mehdi Ali, Charles Tapley Hoyt, Daniel Domingo-Fernández, Jens Lehmann, Hajira Jabeen

bioRxiv 475202; doi: https://doi.org/10.1101/475202

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