Distribution of node and edge types in the custom and OpenBioLink KGs.

Distribution of node and edge types in the custom and OpenBioLink KGs.

<p>The properties of each of the two networks are detailed in <b><a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1009909#pcbi.1009909.s010" target="_blank">S7 Table</a></b>.</p>

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Bibliographic Details
Main Author:	Daniel Domingo-Fernández (5432273) (author)
Other Authors:	Yojana Gadiya (12153037) (author), Abhishek Patel (9442746) (author), Sarah Mubeen (6704834) (author), Daniel Rivas-Barragan (9721575) (author), Chris W. Diana (12153040) (author), Biswapriya B. Misra (6715544) (author), David Healey (12153043) (author), Joe Rokicki (12153046) (author), Viswa Colluru (12153049) (author)
Published:	2022
Subjects:	Genetics Molecular Biology Neuroscience Pharmacology Biotechnology Cancer Mental Health Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> network side effect prediction kg ), guided becoming increasingly popular achieving better performance specific transcriptomic signatures biological data representation transcriptional signatures observed signatures observed omics data target discovery similar methodologies similar applications signature profile prioritizes drugs predictions made perturbation experiment novel algorithm multiple datasets level overview knowledge graph deep characterization based approaches approach identifies
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