Search Results for author: Cheng Ye

Found 3 papers, 2 papers with code

A Knowledge Graph-Enhanced Tensor Factorisation Model for Discovering Drug Targets

no code implementations20 May 2021 Cheng Ye, Rowan Swiers, Stephen Bonner, Ian Barrett

We created a three dimensional data tensor consisting of 1, 048 gene targets, 860 diseases and 230, 011 evidence attributes and clinical outcomes connecting them, using data extracted from the Open Targets and PharmaProjects databases.

BIG-bench Machine Learning Drug Discovery +2

Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery

2 code implementations17 May 2021 Stephen Bonner, Ian P Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Charles Tapley Hoyt, William L Hamilton

Knowledge Graphs (KG) and associated Knowledge Graph Embedding (KGE) models have recently begun to be explored in the context of drug discovery and have the potential to assist in key challenges such as target identification.

Drug Discovery Knowledge Graph Embedding +2

A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective

2 code implementations19 Feb 2021 Stephen Bonner, Ian P Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Andreas Bender, Charles Tapley Hoyt, William L Hamilton

We aim to help guide machine learning and KG practitioners who are interested in applying new techniques to the drug discovery field, but who may be unfamiliar with the relevant data sources.

BIG-bench Machine Learning Drug Discovery +1

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