About BEB
CNC Research
BEB in the Media
Molecular Systems Biology
September 24 - 28
(Armindo Salvador - armindo.salvador@gmail.com, Renata Dias Silva)


(Organizers: Armindo Salvador, Renata Silva)



Oleg Igoshin (Rice University, U.S.A.)

Isabel Rocha (University of Minho, Portugal)

Armindo Salvador (Centre for Neuroscience and Cell Biology, Portugal)

Renata Silva  (Centre for Neuroscience and Cell Biology, Portugal)


Hands-on session tutors

Alessandro Bolli (Centre for Neuroscience and Cell Biology, Portugal)

Pedro Branco (Centre for Neuroscience and Cell Biology, Portugal)

Rui Benfeitas (Centre for Neuroscience and Cell Biology, Portugal)


This module will introduce key concepts and tools in the field of Molecular Systems Biology, with an emphasis on theoretic-experimental integration. Main pedagogic objectives are:

1. To motivate the students for quantitative, integrative and theory-driven biological research.

2. To provide basic background and hands-on training on kinetic modeling, both deterministic and stochastic.

3. To highlight the importance of finding generic organizing principles of biological systems, providing some examples in various domains (metabolism, signal transduction, etc.)

4. To familiarize the students with key concepts for the understanding of biological organization at the molecular level. E.g. stability, robustness, molecular noise, design principles.

The module will have a strong hands-on component where students will investigate the properties of concrete biochemical systems by formulating, simulating and analyzing suitable kinetic models.


Course program and materials

Day 1 (September 24)

Lecturer: Armindo Salvador


9:00-9:30 Course overview

9:30-10:15 Are there laws of Molecular Biology?

10:30-12:00 Design principles of elementary metabolic circuits

14:00-16:00 Introduction to kinetic modeling of biochemical systems: representations of processes and systems

16:15-18:30 Hands-on practice

Materials for days 1 and 2:

Copasi (download from http://copasi.org/tiki-index.php?page=downloadNonCommercial)
Copasi video (courtesy of Oleg Igoshin’s group) http://owlsocrates.rice.edu/Panopto/Pages/Viewer/Default.aspx?id=d0399b8c-5ef0-452e-828a-9816d9b6fec8

Alves, R., F. Antunes, et al. (2006). "Tools for kinetic modeling of biochemical networks." Nature Biotechnology 24:667-672.

Salvador, A. and M. A. Savageau (2006). "Evolution of enzymes in a series is driven by dissimilar functional demands." Proceedings of the National Academy of Sciences of the U. S. A. 103: 2226-2231.

Coelho, P. M. B. M., A. Salvador, et al. (2009). "Quantifying Global Tolerance of Biochemical Systems: Design Implications for Moiety-Transfer Cycles." PLoS Computational Biology 5(3): e1000319.


Milo, R., S. Shen-Orr, et al. (2002). "Network Motifs: Simple Building Blocks of Complex Networks." Science 298: 824-827.

Salvador, A. and M. A. Savageau (2003). "Quantitative evolutionary design of glucose 6-phosphate dehydrogenase expression in human erythrocytes." Proceedings of the National Academy of Sciences of the U. S. A. 100: 14463-14468.

Savageau, M. A., P. M. B. M. Coelho, et al. (2009). "Phenotypes and tolerances in the design space of biochemical systems." Proceedings of the National Academy of Sciences of the U. S. A. 106: 6435–6440.

Coelho, P. M. B. M., A. Salvador, and M. A. Savageau (2010). "Relating Mutant Genotype to Phenotype via Quantitative Behavior of the NADPH Redox Cycle in Human Erythrocytes." PLoS ONE 5: e13031

Bar-Even A, Flamholz A, Noor E, Milo R (2012) "Rethinking glycolysis: on the biochemical logic of metabolic pathways". Nat Chem Biol 8:509-517


Day 2

Lecturers: Armindo Salvador, Renata Silva


9:00-10:15 Introduction to kinetic modeling of biochemical systems: Data sources and approximate representations of kinetics

10:30-12:00 Hands-on practice

14:00-16:00 Introduction to deterministic kinetic modeling of biochemical systems: Steady-states and sensitivity analysis

16:15-18:30 Hands-on practice


Day 3

Lecturer: Isabel Rocha


11:00-13:00 (with breaks as needed): Metabolic Networks: Concepts and Applications

14:00-17:00 (with breaks as needed): Simulation Tools for stoichiometric metabolic models


Day 4

Lecturer: Oleg Igoshin

Schedule (lectures interspersed with hands-on practice, breaks as needed)

9:00-10:50 Bistability (1h lecture +45min practice)

11:00-12:30 Bistability in the lac operon  (1h lecture +30 min practice)

14:00-15:30 Stochastic simulations(1h lecture +30 min practice)

15:30-18:30 Hands-on practice


Novick A, Wiener M. 1957. Enzyme Induction as an All-or-None Phenomenon PNAS  43: 553-566.
Elowitz MB, Levine AJ, Siggia ED, Swain PS. 2002. Stochastic gene expression in a single cell. Science 297: 1183-6


Ozbudak EM, Thattai M, Lim HN, Shraiman BI, Van Oudenaarden A. 2004. Multistability in the lactose utilization network of Escherichia coli. Nature 427: 737-40.

Ray JCJ, Tabor JJ, Igoshin OA (2011) "Non-transcriptional regulatory processes shape transcriptional network dynamics". Nature Reviews Microbiology 9:817-828


Day 5

Lecturer: Oleg Igoshin


9:00-11:30 Stochastic switches (lectures interspersed with hands-on practice, break as needed)


Maamar H, Raj A, Dubnau D. Noise in gene expression determines cell fate in Bacillus subtilis. 2007.Science 317: 526-9.

10:30-12:30 Student presentations of hands-on projects

14:00-15:45 Student presentations of hands-on projects

16:00-17:00 CNC seminar: “Self-organization mechanisms in Myxococcus xanthus biofilms” by Oleg Igoshin (Rice University, Houston, USA)

Myxococcus xanthus is a model bacteria famous for its coordinated multicellular behavior resulting in formation of various dynamical patterns. Examples of these include fruiting bodies – aggregates in which tens of thousands of bacteria self-organize to sporulate under starvation conditions and ripples – dynamical cell density waves propagating through the colony during predation. Relating these complex self-organization patterns to behavior of individual cells is a complex-reverse engineering problem that cannot be solved solely by experimental research. Our group addresses this problem with a complementary approach – a combination of biostatistical image quantification and agent-based modeling.

Important notes
Students are requested to bring their own laptops with Copasi v4.8 installed (download from http://copasi.org/tiki-index.php?page=downloadNonCommercial).
All reading materials are available for download from here: https://docs.google.com/folder/d/0BwdktvkPluE7dGtVcnE1ekZKTzQ/edit (accessible only to lecturers, PDBEB students and registered participants).

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