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Representing Semantified Biological Assays in the Open Research Knowledge Graph
2020, Anteghini, Marco, D'Souza, Jennifer, Martins dos Santos, Vitor A.P., Auer, Sören, Ishita, Emi, Pang, Natalie Lee San, Zhou, Lihong
In the biotechnology and biomedical domains, recent text mining efforts advocate for machine-interpretable, and preferably, semantified, documentation formats of laboratory processes. This includes wet-lab protocols, (in)organic materials synthesis reactions, genetic manipulations and procedures for faster computer-mediated analysis and predictions. Herein, we present our work on the representation of semantified bioassays in the Open Research Knowledge Graph (ORKG). In particular, we describe a semantification system work-in-progress to generate, automatically and quickly, the critical semantified bioassay data mass needed to foster a consistent user audience to adopt the ORKG for recording their bioassays and facilitate the organisation of research, according to FAIR principles.