ACTION on Cancer
Lead Research Organisation:
Goldsmiths University of London
Department Name: Computing Department
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Publications
King R
(2018)
Automating Sciences: Philosophical and Social Dimensions
in IEEE Technology and Society Magazine
Roper K
(2022)
Testing the reproducibility and robustness of the cancer biology literature by robot.
in Journal of the Royal Society, Interface
Roper K
(2022)
Testing the reproducibility and robustness of the cancer biology literature by robot.
in Journal of the Royal Society, Interface
Sadawi N
(2019)
Multi-task learning with a natural metric for quantitative structure activity relationship learning.
in Journal of cheminformatics
Wang K
(2021)
NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding.
in NPJ systems biology and applications
| Description | we are developing new ML tools for improving cancer-relevant predictions |
| Exploitation Route | Cancer patients could be prescribed more effective chemotherapy drug combinations |
| Sectors | Healthcare |
| Description | SkyLab Bio company is using machine learning software developed within this project |
| First Year Of Impact | 2022 |
| Sector | Pharmaceuticals and Medical Biotechnology |
| Impact Types | Economic |
| Description | Arctoris Ltd |
| Organisation | Arctoris |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Our research team provides description of experiments and research hypotheses. This is a test case for Arctoris to develop an interactive system with external researchers. |
| Collaborator Contribution | Arctoris (https://www.arctoris.com/) is contributing to the project by running experiments in their lab. |
| Impact | experimental data |
| Start Year | 2020 |
| Description | Imagen |
| Organisation | Imagen Therapeutics |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | expert advise on the analysis of data |
| Collaborator Contribution | provided unique datasets |
| Impact | datasets |
| Start Year | 2021 |