no code implementations • 28 Mar 2022 • Jennifer D'Souza, Anita Monteverdi, Muhammad Haris, Marco Anteghini, Kheir Eddine Farfar, Markus Stocker, Vitor A. P. Martins dos Santos, Sören Auer
For this in turn, there is a strong need for AI tools designed for scientists that permit easy and accurate semantification of their scholarly contributions.
no code implementations • 30 Nov 2021 • Marco Anteghini, Jennifer D'Souza, Vitor A. P. Martins dos Santos, Sören Auer
Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries.
1 code implementation • 16 Sep 2020 • Marco Anteghini, Jennifer D'Souza, Vitor A. P. Martins dos Santos, Sören Auer
As a novel contribution to the problem of semantifying biological assays, in this paper, we propose a neural-network-based approach to automatically semantify, thereby structure, unstructured bioassay text descriptions.