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Program 2027

Modules and instructors

From the Linux command line to Python, R and the analysis of genomic data: the classes are given by experts in the field and consist of lectures and exercises at the computer. The program is subject to change.

The philosophy of the course is “learning by doing”: computational skills are taught using examples and real data from evolutionary biology. The aim is to provide you with the background and skills to perform computational analyses with a focus on research questions related to genomics and evolution.

Course roadmap

  1. Days 1-4

    UNIX and Python foundations

    Linux command line, Bash scripting, introduction to Python

  2. Days 5-9

    Genomics and analysis

    NGS pipelines, genome assembly, phylogenomics, population genomics

  3. Days 10-13

    R and advanced tools

    Introduction to R, differential gene expression, machine learning, data visualization

  4. Days 14-16

    The capstone

    3-day group projects applying the learned workflows to evolutionary research questions, followed by final presentations

Modules

  • Introduction to Linux systems

    • Isolde van Riemsdijk Copenhagen University, Denmark

  • Analysis of high-throughput sequencing data

    • Vladimir Jovanović Freie Universität Berlin, Germany

  • Genome Assembly

    • Deborah Triant University of Virginia, USA

  • Using AI in programming

    • Deborah Triant University of Virginia, USA

  • NGS for non-model organisms

    • Camila Mazzoni Berlin Center for Genomics in Biodiversity Research, Berlin, Germany

  • Phylogenomics

    • Iker Irisarri Museo Nacional de Ciencias Naturales (CSIC), Madrid, Spain

  • Introduction to R and statistics

    • Rik Verdonck Universiteit Hasselt, Belgium

  • Machine Learning

    • Deisy Gysi Federal University of Paraná, Brazil

  • Comparative analysis of expression data

    • Stefano Berto Medical University of South Carolina, USA

  • Introduction to Python

    • Deborah Triant University of Virginia, USA

  • Population genomics

    • Susanne Pfeifer Arizona State University, USA
    • Sandra Oliveira University of Zurich, Switzerland

  • Visualization of scientific data

    • Jan Aerts Katholieke Universiteit Leuven, Belgium

  • 3-day final project

    You can propose a project of your own interest and, if appropriate, your own data. A selection of projects will be chosen and carried out under the supervision of a teaching assistant.

A typical day

TimeActivityDescription
7:30-8:45 a.m. Breakfast At the hotel, included in the fee
9:00-10:30 a.m. Warm-up lecture and concepts Foundational theory
10:30-10:45 a.m. Coffee and discussion
10:45 a.m.-12:00 p.m. Hands-on coding lab Guided exercises with real biological datasets
12:00-1:30 p.m. Lunch break
1:30-3:00 p.m. Afternoon deep-dive Advanced exercises and problem sets
3:00-3:15 p.m. Coffee and discussion
3:15-5:45 p.m. Afternoon deep-dive Continue with advanced exercises
6:00-7:00 p.m. Dinner break
(7:15-9:00 p.m.) Hack/study time Depending on the day: self-study with teaching assistants or an evening lecture

The course starts at 9 a.m. on the first day, Saturday, March 6.

Special days

  • Arrival day, March 5: informal get-together in the evening to meet the other participants
  • Free day: a choice of optional activities, such as sightseeing, a bus tour of Berlin or a visit to the zoo, all free of charge for participants
  • Final dinner and goodbye: a relaxed evening with a joint dinner at a restaurant and a light program

Apply for March 2027

The course is limited to approximately 25 participants. Applications are sent as a single PDF by email. Application deadline: October 21, 2026.

How to apply