Ecological Complexity Lab Elucidating the complexity of ecological systems

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Course details

Course name: Analysis of ecological-biological networks

Course number: 205-2-1609

Lecturer’s name: Shai Pilosof, pilos@post.bgu.ac.il

Course Structure: Lecture: 2 hours Exercise: 2 hours Total # of Points: 3

Course schedule: Sunday to Thursday 23-27/2/2026, 8:00-17:00, and 12/3/2026 8:00-16:00 Sde Boker campus.

Teaching method: The course is given entirely in English, in person (no zoom or hybrid classes). Students will be actively engaged through paper discussions, and because of the interactive format, enrollment is limited to 10 students. All classes, discussions, and presentations will be conducted in English, and students are encouraged to use their own research data for the final project.

Course description

Biological systems, and specifically ecological systems, consist of multiple interconnected entities that form networks such as gene interaction networks, food webs, plant–pollinator networks, metapopulations, and disease transmission networks. Understanding how these networks are structured is crucial for understanding the dynamics and functioning of biological systems. This course introduces the theory and methods for analyzing biological networks, with a primary emphasis on ecology but with applications extending to neuroscience, systems biology, and epidemiology. While examples and theory are drawn from ecology, the course is general in scope, reflecting the broad relevance of network science across biology.

The course is dynamic and adapted to students’ needs as much as possible. Course material may vary from what is currently written in the syllabus at the instructor’s discretion.

Course goals

Provide students with:

  1. An understanding of the (ecological) theory underlying the structure and dynamics of complex systems.
  2. Tools to perform network analysis on a variety of network types.
  3. Skills: programming and analysis of network data, advanced paper reading, presenting research, scientific writing.

Main course Topics

Academic and general requirements and prerequisits

  1. The only prerequisite is prior knowledge in programming. LLM-knowledge in programming does not count! Exercises are written in R. Students who wish to program in another language may do so independently.
  2. An introduction to ecology course is recommended, but not required.
  3. Knowledge in linear algebra is recommended, but not required.
  4. The exercises are computational, and students are required to bring a laptop.

Course requirements and grading

Details on course assignments:

Labs

Labs are not for submission BUT it is difficult to understand the material without hands-on analysis. Recommendation: apply the labs to your own data whenever possible. Lab topics are not completely compatible with class topics.

To do the labs you must have R + RStudio installed on your laptop. Please come ready, already to the first class.

Projects

The goal of a project is to provide you with real-life experience on how to use network in research. You are encouraged to select a project that will advance your own research.

Project types:

Final report: The goal of the final report is for you to practice and improive scientific writing. The final report will be 1500-2000 words with up to 3 figures. Reviews will be max 2500 words and 3 figures. Submit the final report by email to me. The final report is due on 21/3/2026.

Presentations

Presentations are on 12/3/205. Project presentations are in a conference style:

Paper discussions