BLOGS
NeuralKG on DrugBank
Author: NeuralKG Core Team Date: 2022.03.21
Drug Repurposing Knowledge Graph on NeuralKG
Author: NeuralKG Core Team Date: 2022.03.21
Drug Repurposing Knowledge Graph (DRKG) is a comprehensive biological knowledge graph relating genes, compounds, diseases, biological processes, side effects and symptoms. DRKG includes information from six existing databases including DrugBank, Hetionet, GNBR, String, IntAct and DGIdb, and data collected from recent publications particularly related to Covid19. It includes 97,238 entities belonging to 13 entity-types; and 5,874,261 triplets belonging to 107 edge-types.[more]
Gene Ontology with NeuralKG
Author: NeuralKG Core Team Date: 2022.03.21
NeuralKG for Recommendation
Author: NeuralKG Core Team Date: 2022.03.17
It is worth mentioning that NeuralKG’s use is not limited to the standard benchmarks such as FB15K237, WN18RR. We could construct self-defined Knowledge Graphs datasets and get strong baseline for more comprehensive experiments with NeuralKG. We could use an example to illustrate how to apply NeuralKG on self-defined datasets. [more]
Brief Introduction to NeuralKG
Author: NeuralKG Core Team Date: 2022.03.01
NeuralKG is an open-source Python-based library for diverse representation learning of knowledge graphs. It implements three different series of Knowledge Graph Embedding (KGE) methods, including conventional KGEs, GNN-based KGEs, and Rule-based KGEs. With a unified framework, NeuralKG successfully reproduces link prediction results of these methods on benchmarks, freeing users from the laborious task of reimplementing them… [more]