Computational biology II: assessment

You will be assessed through:

• Quizzes during the lectures: 25% of the grade
• Programming labs: 25% of the grade
• A small project OR an article presentation: 50% of the grade

Programming labs

To be done individually or in pair of students. Send a jupyter notebook to the lecturer (antoine.frenoy@univ-grenoble-alpes.fr) containing your code and graphs with comments before the deadline. Beyond programming, pay attention to the quality of the graphs and their interpretation (you must clearly describe them and conclude).

• Lab 1, deadline 2025-11-25
• Lab 2, deadline 2025-12-08, can be extended up to 2025-12-15

Common rules for project OR article presentation

• You will indicate here your choice of team and activity (project or one of the proposed articles), before 2025-11-25.

• You can work alone or in a team of two students.

• 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.

• The deadlines are strict. You will send me your work by email (and I will systematically acknowledge receipt).

• If you choose to present an article: articles are assigned on a first-come first-served basis. The presentation date is constrained by the article choice (because the articles presentations are part of the lecture and are thus synchronized with the advancement).

• All information needed for the project will be covered by the end of third lecture. All information needed for article presentation will be covered by the end of the lecture before the presentation date.

• 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.

Project

The goal is to design and implement simple individual-based simulations of evolution, and use it to study phenomena discussed during this course.

Suggested ingredients and design choices of the model:

• The model will feature simple demographics (you can for example use a non-neutral Moran process; varying population size is also possible but harder to implement)
• Mutations can occur, and the distribution of their effects should be realistic (in particular, it is important to also include the possibility for deleterious mutations, not only beneficial ones)
• Genotypes can be very abstract (they will not accurately mirror bacterial genomes), and do necessarily need to be explicitely represented. An individual could for example be represented as a list of traits (in which case genotype = phenotype). The central ingredient will be to choose a genotype / phenotype to fitness map, and you can for example use Fisher Geometric Model (discussed in class, this is the simplest option) or Stuart Kauffman’s NK model (slightly more complex). It is also possible to use empirical datasets (ask the lecturer if you want to know more).

Research question: beyond a general illustration of evolutionary dynamics, you will use this model to study one or sereval specific questions. A few possible suggestions:

• Selection for or against mutator alleles (Chao and Cox, 1983, Taddei et al, 1997).
• Effect of ruggedness of the fitness landscape
• Effect of environmental changes in time
• Effect of environmental heterogeneity in space
• Effect of spatial structure
• Punctuated equilibrium / cohort of mutations (vs more continuous accumulation of mutations)
• Clonal interference

You can also study any other phenomena discussed during the class if the model is suitable.

You will send a short report, which should clearly describe your modeling choices as well as the questions you chose to focus on and the obtained results (with relevant figures). Strict deadline: 2025-01-16 2025-01-23.

Article presentation

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 12 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.

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 project. A substantial reading 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.

• Mutation dynamics and fitness effects followed in single cells (Robert et al, 2018), presentation on 2025-12-09

• A systems analysis of mutational effects in HIV-1 protease and reverse transcriptase, presentation on 2025-12-09

• Wide lag time distributions break a trade-off between reproduction and survival in bacteria (Moreno-Gamez et al, 2020), presentation on 2025-12-09

• The first steps of adaptation of Escherichia coli to the gut are dominated by soft sweeps (Barroso-Batista et al, 2014), presentation on 2025-12-16

• A rugged yet easily navigable fitness landscape (Papkou et al, 2023), presentation on 2025-01-07, presentation on 2025-12-16

• Mutation rate of SARS-CoV-2 and emergence of mutators during experimental evolution (Amicone et al, 2022), presentation on 2025-01-06

• The evolution of stress-induced hypermutation in asexual populations (Ram and Hadany, 2012), presentation on 2025-01-06

• Evolution of evolvability in gene regulatory networks (Crombach and Hogeweg, 2008), presentation on 2025-01-13

• Pervasive selection for cooperative cross-feeding in bacterial communities (Germerodt et al, 2016), presentation on 2025-01-13

• Emergent cooperation in microbial metabolism (Wintermute and Silver, 2010), presentation on 2025-01-13