Description
Given the increasingly complex systems used, and vast amounts of data accumulated by scientific research, interdisciplinarity is essential in the effort to generate new knowledge and to drive innovation. Computational Cell Biophysics is a 15-credit level 7 module designed to encourage students to take an interdisciplinary approach to cell biology. In particular, the goal of the module is to provide students with a conceptual and quantitative understanding of areas of Physics that are relevant to Biology. The module will encourage students to broaden their horizons by making connections between ideas and concepts across different disciplines, as well as learn numerical and computational programming skills in Python. The module provides research-led teaching by Ïã¸ÛÁùºÏ²Ê scientists working at the interface of cell biology and physics. Core concepts in physics (themes), illustrated by relevant biological phenomena, will beÌýintroduced in face-2-face lectures. Students then explore the extent to which the analysis is generalizable across systems and scales using custom designed on-line exercises. Finally,Ìýworkshops, in which students present the results of the online exercises, reinforce the learnt material and provide the opportunity for discussion.
Four themes each consisting of lectures, on-line exercises and workshops will explore:
1. Mechanics across Scales – from molecules to tissues
2. Noisy Processes and their Analysis
3. Signalling / Networks
4. Image Analysis / Maching Learning / AI
Workshops will additionally provide students with; a short introduction to numerical Python; information on how to best to read and critique research papers; as well as providing specific advice on coursework assessments. The assessment for the module is coursework and consists of a review of one of the module themes. Students present their paper in a short (15min) presentation and together with students researching the same topic collaboratively construct a website resource on the topic.
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 19th August 2024.
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