"Cell Dynamics: from molecules and movies to medicine" with Professor Viji Draviam and Dr David Dang
Date: 25 February 2021 Time: 11:00 - 12:00
The Institute of Applied Data Science welcomes Professor Viji Draviam, Professor of Quantitative Cell and Molecular Biology, and Dr David Dang, both from School of Biological and Chemical Sciences, Queen Mary University of London. Viji also serves as Director of Industrial Innovation at School of Biological and Chemical Sciences.
Viji's research is aimed at understanding how cytoskeletal forces are generated and controlled within human cells. The group reported novel microtubule-mediated events that operate during human cell division: (i) the end-on conversion process, through which human chromosomes captured along lateral walls of microtubules are brought to the ends of microtubules, without detachment, and (ii) previously unrecognized cortical Dynein-independent and microtubule-dependent mechanisms that maintain the position of spindle.
Viji's current research focus is dedicated to understanding (i) how human chromosomes are accurately segregated and (ii) how the plane of cell division is correctly defined. For this purpose, Viji's research group combines live-cell microscopy with molecular, computational and biochemistry techniques. In addition to uncovering fundamental cell division mechanisms, findings have been useful in the context of diseases: to explain molecular lesions that promote aneuploidy (irregular chromosome numbers) – a common feature of aggressive cancers and to develop drug re-positioning strategies for identifying new microtubule-targeting drugs.
David recently finished his PhD research project: "Computational tools to measure, model and modulate Human Spindle Movements". This project summary is presented below:
Accurate positioning of mitotic spindles is important for proper cell division and tissue development. While it is known that dynein generates pull forces that are needed for spindle rotation, it remains unclear how the center of rotation is governed in human cells. To investigate spindle movement through time and space, a sophisticated computational analyzing regime is required to fully explore the pattern embedded in live-cell time lapse images.
With a background in Statistics and Computer Sciences, David is currently developing the SpinX software using state-of-the art technologies in Machine Learning to precisely predict the position of the the spindle, and is currently translating research outputs from his PhD project by working collaboratively with an industrial project partner.
Join us at 11am via the Zoom channel https://turing-uk.zoom.us/j/783073281
|Location:||Webinar via Zoom|
|Contact:||Dr Gareth Tyson|
Updated by: Michal Filus