Metabolic Network Analysis - 2019
The course discusses the mathematical modelling of large
networks, metabolic networks in particular, and the subsequent
contrained-based analysis of their dynamic properties. Focus will be on
the mathematical underpinning and algorithms involved. We introduce the
fundamental concepts of the stoichiometric matrix and flux vector and
show what information can already deduced from the first, 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 software
packages that implement these (e.g. CellNetAnalyzer). The concepts are
applied to the problem of optimal metabolite production for a model
organism. If time permits, parametric sensitivity is discussed.
The course targeted at students in the Life Sciences,
and Bioinformatics. The topics will be dicsussed in a well-balanced
mixture of biology, biochemistry, mathematics and computer science.
Examination will be by means of assignments that students need to make
individually, and final team assignments in which in a small
interdisciplinary team specially selected research papers on
applications of metabolic network analysis are studied. The results are
presented to the other students. The team presentation and a written
report of the study are evaluated. The results of individual
assignments, team presentation and team reports are combined to obtain
the final grade.
The course was initially based on: 'Systems Biology: properties of reconstructed networks',
O. Palsson, Cambridge University Press, 2006 (ISBN-13 978-0-521-85903-5)
This book may still be helpful, but not essential for following the course.
However, in its latest version the course is based on various papers from the scientific literature instead. References will be provided during the lectures and in the lecture notes of the course. These will come available piece by piece on this website.
- The course starts on Tuesday, 5th February 2019, 11:00-12:45h in room 401 of the Snellius building.
- There are differences between the lecture schedule for the course stated in the Mathematics curriculum and in that of Computer Science.
Therefore, we take an 'intersection' of both:
Lectures take place weekly from 11:00-12:45h in room 401 until 13th May 2019.
On 12th March, 16th April, 23rd April and on 21st May there are no lectures.
Slides of lectures:
- Lecture 1: Course introduction [pdf]
- Lecture 1: Modelling biochemical reaction networks [pdf]
- Lecture 2: Modelling biochemical reaction networks II [pdf]
- Lecture 2: Network statistics [pdf]
Lecture Notes (subject to updates):
An updated version of the Lecture Notes becomes available section-wise
during the course.
- Front matter (title page and table of contents)
- Appendices: A) Linear Algebra and B) Fundamental properties of convex cones [pdf] (164 kB, vs. of 4 Feb 2019)
- Bibliography [pdf] (31 kB, vs. of 4 Feb 2019)
Assignments are sent to the students by email and become available on this
website too during the
Individually written essay on selected research papers (30%):
- First Assignment (15%):
- Second Assignment (15%):
Students will be alllocated to small teams of 2-3 students that study a collection of research papers. Each team member will write an essay individually (max. 10 pages A4) on a specific research question related to the collection of papers.
The deadline for this essay will be announced.
Team presentations (10%):
The teams mentioned above will present togerther, in a joint presentation, for all course attendees their interpretation of the results presented in the collection of papers assigned to the team. A date for a final presentation session of team presentations on
various topics on Metabolic Network Analysis will be agreed upon by the participants
during the lecture.
The most convenient date and time of the final presentation session will be determined with the students during the course.
Written exam (30%):
The date, time and location of the written exam still needs to be determined. It will be annouced as soon as possible.
The final grade for the course is computed as the weighted average of the various parts of the examination, with weighting as indicated above.
Final presentation topics and papers:
Will be announced.
Details will be announced.
page was last
updated: 11th February 2019