David Healey

Orcid: 0000-0002-9584-9757

According to our database1, David Healey authored at least 9 papers between 2020 and 2024.

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Bibliography

2024
Evaluating the generalizability of graph neural networks for predicting collision cross section.
J. Cheminformatics, December, 2024

2023
Exploring the known chemical space of the plant kingdom: insights into taxonomic patterns, knowledge gaps, and bioactive regions.
J. Cheminformatics, December, 2023

On the correspondence between the transcriptomic response of a compound and its effects on its targets.
BMC Bioinform., December, 2023

Efficiently predicting high resolution mass spectra with graph neural networks.
Proceedings of the International Conference on Machine Learning, 2023

2022
Causal reasoning over knowledge graphs leveraging drug-perturbed and disease-specific transcriptomic signatures for drug discovery.
PLoS Comput. Biol., 2022

Multi-scale Sinusoidal Embeddings Enable Learning on High Resolution Mass Spectrometry Data.
CoRR, 2022

The role of living laboratories in unlocking the potential of low-carbon energy technologies on the journey to net-zero.
CoRR, 2022

Ensembles of knowledge graph embedding models improve predictions for drug discovery.
Briefings Bioinform., 2022

2020
Deep Reinforcement Learning-Based Energy Storage Arbitrage With Accurate Lithium-Ion Battery Degradation Model.
IEEE Trans. Smart Grid, 2020


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