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
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