Introduction
The aim in this project is to build upon the success of our foundational work and lead an ambitious and integrated effort to build new AI/ML methods that bridge molecular and cellular scale features and enable a genotype-to-phenotype level understanding of biology. This will drive future scientific discovery and facilitate an unprecedented view of the function and organisation of living matter.
Explaining the science
We are building state-of-the-art tools for synthetic data generation and methods to learn molecular representations, scaling existing models to larger, real-world, datasets and will deploy and develop the models with the community.
Applications
We will build upon our existing work in this domain (in collaboration with MRC-LMB, Cambridge, STFC) and our new partnership with the Franklin, to develop an integrated effort to build new AI/ML methods that bridge molecular and cellular scale features, enabling an unprecedented view of the function and organization of living matter.
This will make use of data from the new state of the art, and currently only instrument in the world, at Franklin, which will potentially open up major new research in biomedicine and fundamental life sciences.
Researchers and collaborators
Dr Camila Rangel Smith
Senior Research Data Scientist
Dr Alden Conner
TPS Senior Researcher, Research Applications