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Metabolic Network Analysis (BM)


Admission requirements

Elementary calculus, some basic knowledge of linear algebra is useful (e.g. matrix addition, matrix multiplication).


The course discusses rationales and methods for the mathematical modelling of large biochemical networks, metabolic networks in particular, and the subsequent contraint-based analysis of their dynamic properties. We introduce the concepts of the stoichiometric matrix and flux vector and show what information can already be deduced from them, e.g. concerning possible steady state flux vectors for the system: extreme pathways, elementary modes and the relationships among the two. Several algorithms will be explained for computing them, together with hands-on exercises using software packages implementing these algorithms (e.g., CellNetAnalyzer, Cobra). The concepts are applied to the problem of optimal metabolite production for bacteria, the Warburg effect in mammalian (tumor) cells, metabolic regulation of multicellular organisms, and the dynamics of microbial ecosystems.

Course objectives

  • Learn to work with graph representation of (bio)chemical reaction networks, analysis methods and algorithms for computing flux balance analysis, elementary flux modes, extreme currents, and data integration techniques.

  • Understand the approaches and limitations of the modelling method, read and understand current research on the topic.

  • Learn to approach biological questions on metabolism using flux-balance analysis.


The most recent timetable can be found on the students' website.

Mode of instruction

Homework assignments
Team projects

Assessment Method

Individual assignments/homework (30%)
Individually written essay (30%)
Team projects with team presentation (10%)
Written exam (30%)

Reading list

The course has lecture notes that will be made available. Various research papers will be distributed during the course.
Optional: Students may consult B.O. Palsson, Systems Biology: properties of reconstructed networks, Cambridge University Press, 2006 (ISBN 0-521-85903-4). It provides a broad view on the topic, but it is limited to Extreme Pathway analysis. It is not required.


  • You have to sign up for courses and exams (including retakes) in uSis. Check this link for information about how to register for courses.


Lecturer: Dr. E. Tsingos
Email: e.tsingos[at]math.leidenuniv.nl
Website: See the Brightspace page for the course


For all material and up-to-date information about the course see the Brightspace course page.