Introduction to Computational Systems Microbiology
Graduate School of Health and Medical Sciences at University of Copenhagen
This course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD Students from NorDoc member faculties. All other participants must pay the course fee.
Anyone can apply for the course, but if you are not a PhD student at a Danish university, you will be placed on the waiting list until enrollment deadline. This also applies to PhD students from NorDoc member faculties. After the enrollment deadline, available seats will be allocated to applicants on the waiting list.
Learning objectives
A student who has met the objectives of the course will be able to:
1) describe a simple biological system with mathematical models
2) simulate and analyze different types of mathematical models
3) interpret data quantitative for hypothesis testing
4) have insight into complex biological processes through joint mathematical-experimental approaches
Content
The course introduces a variety of computational/mathematical techniques for modeling and analysis of biological systems. Topics include properties of gene-regulatory and signaling networks; network reconstruction from data; stochastic modeling to study single-cell variation, and physiological modeling. Emphasis will be on using computation techniques as an in-silico tool for guiding experimental design.
The course will apply the following mathematical techniques: Boolean models, Bayesian networks, Metabolic flux balance, Agent-based models, ODEs, PDEs, and Stochastic modeling to study biological systems at different spatial scales. These systems include gene regulatory networks, metabolic and protein networks, cellular and ecological population dynamics, and tissue and organ level modeling. Applications to industrial/medical biotechnology, gene network reconstruction, and analysis of omics data will be discussed. Also covered will be general introductions to bacterial viruses, phages, as well as to major topics within antibiotic resistance.
The following topics will be covered:
• Introduction to Systems Biology and show examples of well-known mathematical models in molecular and cell biology, neuroscience, ecology, and evolution.
• Introduction to Boolean models of gene regulatory networks and tools for inferring gene interactions from expression level data. Hand-on exercises on model simulation and identification from data. Presentation and discussion on previous papers using Boolean models in the context of modeling different biological pathways
• Modeling gene expression process using different equation models. Hand-on exercises on simulating these models in Microsoft Excel, R, MATLAB, and Mathematica, Discussion of how key parameters (transcription/translation rates, mRNA/protein decay rates) are measured and their genome- wide physiological values from bacterial to mammalian cells.
• Expanding simple gene expression models to consider simple and complex regulation, such as anauto-regulatoryloopwhereproteinsinhibit/activatetheirowngeneexpression. Case studies of examples from literature modeling gene regulation to understand their biological function, and model validation from further experiments.
• Design principle of biological network from feedback to feedforward loops. Motif detection in large biological networks. Function roles of these types of regulation, and how they modulate the dynamic responses of biological systems. Case studies of these motifs in the context of sugar utilization in E. coli and phage lysis of host bacterial cells.
• Introduction to biological toggle switches, clocks with different modeling approaches. Detailed case studies of the lysis-lysogeny switch in lambda phage, cellular decision-making in human viruses and stem cell differentiation. Different types of feedback motifs leading to oscillatory dynamics with examples drawn from circadian clocks in prokaryotes /eukaryotes and molecular oscillators associated with vertebrate somitogenesis.
• Focus on single-cell biology and heterogeneity that arises even within the same isoclonal population. The experimental approach to quantify this cell-to-cell variation. Stochastic modeling of gene expression and regulation to understand the origins and consequences of inter-cellular variation. These results will be connected to bet-hedging behaviors in bacterial and cancer cells with important implications for the emergence of drug resistance.
• Spatial modeling approaches using both partial differential equations and agent-based modeling. Connecting these models to a range of biological phenomena from morphogen gradient formation, chemotaxis, and spatial models for viral-host interactions.
• In addition, a group project will be conducted where 2-3 students share a topic for which modelling is applied. The topic can be selected from their own PhD projects or from a topic addressed in the course.
Participants
The participants will be PhD students from the graduate programs as well as PhD at the graduate program at Science, UCPH. Also, it will be relevant for PhD students at nearby universities including Technical University of Denmark and Lund University.
Basic background in linear algebra and programming. A background in cell/molecular biology will be helpful but not required for the class. Additional mathematical/biological reading material may be given to individual students to bring their background at par with the class.
Relevance to graduate programs
The course is relevant to PhD students from the following graduate programs at the Graduate School of Health and Medical Sciences, UCPH:
Molecular Microbiology and infection
Public Health and Epidemiology
Biostatistics and Bioinformatics
Language
English
Form
Lectures, group work and discussion
Course director
Hanne Ingmer, Professor, Department of Veterinary and Animal Sciences, hi@sund.ku.dk
Teachers
Abhyudai Singh, Professor at University of Delaware, absingh@udel.edu
Hanne Ingmer, Professor, SUND, hi@sund.ku.dk
Ifigeneia Kyrkou, Post doc SUND, ifigeneia.kyrkou@sund.ku.dk
Thomas Ponten, Professor, SUND,
Dates
21/9-25/9 2026
Course location
Frederiksberg Campus, UCPH.
Registration
Please register before 15/8 2026
Expected frequency
Initially considered to be a one-time course but after the first round we are running a second time.
If the course is recurrent and held at specific times each year, or you already know when the course is scheduled to be held again, you can state it here.
Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules.
Applications from other participants will be considered after the last day of enrolment.
Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.