Welcome!
This is the second part of the computational biology class (MSIAM & ENSIMAG).
This class covers biological topics centered around populations, interactions and evolution. These topics will be presented in a computational form, with the goal of modeling and simulating the studied biological processes.
There will be a focus on implementation (with time left for this during some of the lectures), which will rely on several mathematical and computational tools. Some of them (basic probability and statistics, ordinary differential equations, basic programming in Python) are supposed to be already known. Others (stochastic simulations) will be presented alongside the lecture.
We will also read and discuss a selection of research articles. Some of them will be presented by students. These presentations (as well as the assigned readings) are part of the lecture.
Attendance is expected. Hoping to succeed the assessment without attending class is illusory: the assessments are connected with the class, and are certainly not mere programming or data analysis projects.
The slideshows mostly contain illustrations (data, figures, pictures, references, etc) for the lecture. They do not replace notetaking: most of the ideas are explained orally and on the white board.
Here is the list of articles that were proposed for the article presentation, but were not picked. This is my personnal selection of important (and readable) articles in quantitative microbial evolution, specially intended to persons with a mathematical and computational background and an interest for evolutionary biology.
Wide lag time distributions break a trade-off between reproduction and survival in bacteria (Moreno-Gamez et al, 2020), presentation on 2023-11-21
Rate and molecular spectrum of spontaneous mutations in the bacterium Escherichia coli as determined by whole-genome sequencing (Lee et al, 2012), presentation on 2023-11-28
The First Steps of Adaptation of Escherichia coli to the Gut Are Dominated by Soft Sweeps (Barroso-Batista et al, 2014), presentation on 2023-12-05
Pervasive Selection for Cooperative Cross-Feeding in Bacterial Communities (Germerodt et al, 2016), presentation on 2023-12-12
The evolution of stress-induced hypermutation in asexual populations (Ram and Hadany, 2012), presentation on 2023-12-19
You will be assessed based on your work (alone or in a team of two students) on one of the following tasks, following the poll that you answered before the second class.
Beyond this choice of project or article for the assessment, you are all encouraged to read the proposed articles and work on the data challenge and the research project. But you will only be evaluated on one of these works.
General rules:
The deadlines (indicated below) are strict. You will send me your work by email (and I will systematically acknowledge receipt).
If you choose to work as a team of two students, both will get the same grade, with no exception. It is up to you to agree on the way you will work together (division of labor, logistics, etc). The instructor will not arbitrate conflicts between team members.
Each team is expected to produce its own work. Sharing work between teams as well as using code, text or data written or generated by someone else (or by a software) is strictly forbidden. One exception: you are allowed to use figures from the articles as well as other articles you find relevant, but they must be properly referenced. Ideas and information found in other works and used in your work must also be properly referenced.
Download the instructions and dataset here for this data challenge. Keywords: mutagenesis; stochastic simulations; data analysis; parameter inference.
Strict deadline: 2024-01-07. Bonus points for early submission : +1/20 if submitted before 2023-12-22.
You will design and implement an individual-based simulated model to study the adaptation of bacterial populations. Example questions one could study include:
You will have to choose a representation of genotypes and phenotypes suited for the specific question you want to study. To be interesting, your model should probably exhibit some degree of epistasis.
This project requires frequent interactions with the lecturer to define a specific research question and validate your research methodology.
Strict deadline: 2024-01-14. Bonus points for early submission : +1/20 if submitted before 2024-01-07.
You will choose an article among the list below (on a first come first served basis) and present it in front of the class (max 15 min presentation + 5 min questions). Your presentation should include a broad overview of the topic, explain the impact of the ideas and the connection with the class, and make the main ideas understandable by a non-specialist audience. The target audience is the other students of the class (math and cs students), not the lecturer.
In addition to your presentation, you will write a ~1000 words synthesis presenting these points (once again you are not only expected to explain the content of the article, but also to present the broader scientific context and the specific connections with the content of the lectures).
There is no flexibility in the choice of date for the presentations as they have to be synchronised with the advancement of the lectures. You will email me your written synthesis and the slides for your presentation (both as pdf files) 24h before your presentation at the latest.
Beware that presenting a research article is not an easy task, and the article presentation should not be considered as an easy alternative to the data challenge or research project. A substantial reading (and writing) work is expected. It is likely that you will have to read further than the original article to be able to fully understand it and its scientific context.
FYI, the eval grid I use for the presentations is available here.
antoine DOT frenoy AT univ-grenoble-alpes.fr