Artificial Intelligence for Quantitative Biology
We are integrating AI into the process of scientific discovery.
Optics, imaging and microscopy
We are developing super-resolution microscopy and single particle tracking approaches to study reactions in living cells. We are also interested in understanding larger scale functional and phenotypic changes in populations of cells using low photo-toxicity time-lapse imaging.
CellX
CellX is an interdisciplinary project to use automated microscopy, 'omics data, mathematical modelling and artificial intelligence to reverse engineer competitive interactions in cell populations.
Research
The major goal of our research is to identify the principles and mechanisms by which an ensemble of molecules or cells generate particular dynamic temporal or spatial patterns, and how complex functions emerge from that organisation. We are integrating AI into the process of scientific discovery.
Team
We are an experimental biophysics lab comprising a team of physicists, computer scientists and biologists. We create and develop state-of-the-art quantitative imaging and measurement tools and use them to determine how biological machines and systems function.
Publications
We have used single-molecule approaches to study the dynamics of proteins and protein complexes. We developed super-resolution microscopy and single particle tracking approaches to study reactions in living cells. We are using AI and automated microscopy to study cell interactions.
Tools
We have been developing software for image classification, segmentation and tracking, based on computer vision and machine learning approaches to data analysis. We also build our own imaging hardware.
CellX
CellX is an interdisciplinary project to use automated microscopy, 'omics data, mathematical modelling and artificial intelligence to reverse engineer competitive interactions in cell populations.
University College London
Gower Street
London, WC1E 6BT
UK