Search Results for author:
Found 4 papers, 4 papers with code
OntoMerger: An Ontology Integration Library for Deduplicating and Connecting Knowledge Graph Nodes
Duplication of nodes is a common problem encountered when building knowledge graphs (KGs) from heterogeneous datasets, where it is crucial to be able to merge nodes having the same meaning.
ChemicalX: A Deep Learning Library for Drug Pair Scoring
In this paper, we introduce ChemicalX, a PyTorch-based deep learning library designed for providing a range of state of the art models to solve the drug pair scoring task.
A Unified View of Relational Deep Learning for Drug Pair Scoring
In recent years, numerous machine learning models which attempt to solve polypharmacy side effect identification, drug-drug interaction prediction and combination therapy design tasks have been proposed.
MOOMIN: Deep Molecular Omics Network for Anti-Cancer Drug Combination Therapy
We propose the molecular omics network (MOOMIN) a multimodal graph neural network used by AstraZeneca oncologists to predict the synergy of drug combinations for cancer treatment.
