911±¬ÁÏÍø

Content:

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.ÌýComputational Cell BiophysicsÌýis 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.Ìý

Teaching delivery:

The module provides research-led teaching by UCL scientists working at the interface of cell biology and physics. Core concepts in physics (themes), illustrated by relevant biological phenomena, will be introduced 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.ÌýFinallyÌýworkshops, in which students present the results of the online exercises, reinforce the learnt material and provide the opportunity for discussion.

Indicative topics:

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 / MachineÌýLearning / 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.

Module Aims:

To demonstrate to students the power of interdisciplinary approaches to the study of cell biology and to train them to integrate and compare the approaches,ÌýinsightsÌýand methods between two or more disciplines.

Ìý

SpecificallyÌýthe module will:

• provide students with an understanding of how to frame a biological observation as a physicalÌýproblem
• train students to identify and develop appropriate theoretical frameworks to answer cell biologicalÌýproblems
• teach students how to analyse experimentalÌýdata
• teach students to generalize findings across systems and to understand the dependence of biological phenomenon on time and length scales.
• teach students numerical and programmingÌýskills

Learning Outcomes:

By the end of the module students will have acquired a unique skill set and will be expected to be able to:

1. Understand how core concepts in physics can facilitate biological research.
2. Appreciate the advantages and disadvantages of interdisciplinary approaches in cell biological research.
3. Critically evaluate the scientific literature and appreciate how data can be extracted from experimental systems, and how toÌýanalyzeÌýsuch data.
4. Interpret experimental data and design experiments.
5. Write Python code to quantitatively analyse data, build models, run simulations.
6. Communicate scientific information orally, in written form and via websites.

Ìý

Module Organizer:ÌýProf. Yanlan Mao;ÌýÌýSecondary Module Organizer:ÌýProf. Julie Pitcher.