Venue:Systems biology is a growing area of research in Europe and several countries, e.g. Germany and Netherlands, have invested substantial sums of money in significant programmes in this area. This rapid expansion of interest in the area has resulted in an urgent need for experts able to handle the huge amount of data generated, at different levels, and to integrate it in useful models that permit simulation of cell machinary networks and a better understanding of life mechanisms. Biology (including molecular biology) has relied on qualitative and verbal modes of reasoning and explanation, but the human brain cannot be relied upon to model such complex systems intuitively. Integrative systems biology demands that all premises in the explanation are made explicit, modes of interaction of components are given a functional form, and the evolution of the system behaviour simulated on this basis. There are some important features and merits of this approach. One of the aims is to take important knowledge in the form of qualitative biological theories and try to express this as explicitly and quantitatively as possible. Thus, implicit knowledge can be transformed to become explicit knowledge and disparate human knowledge can accumulate in an integrated way.
This approach also tries to model the dynamic behaviour of the system. Life systems are inherently dynamic, but papers or books cannot fully express the dynamism. Computer models can handle and visualize such dynamic behaviour. Thirdly, this approach will make us recognize, the lack of knowledge through model building. There are many unknown pathways or mechanisms and also unknown parameters that govern the mechanisms. Conducting research or measurement of those unknown regions per se is one of the merits. Simulation can identify missing components. Furthermore, we can propose appropriate designs of experiments with the insights from such simulations.
Outline of the course:
The ultimate goal of this course is to give the basic tools and concepts that will permit the student to acquire the basic skills to attain in their future scientific carriers expertise in constructing step by step "Cell Simulators", thorough modelling hierarchically the signal and metabolic networks. The course is intended not only to give a theoretical background but also a practical initiation in modelling metabolic and signalling networks using tools specifically designed to handle problems such as modelling of metabolic and signal transduction (e.g. SCAMP, ESSYNS, GEPASI, JARNAC, SCRUMPY).
Aim of the course:
The course will permit the students to initiate access to Basic concepts on network modelling, with special focus on metabolic and signal transduction networks modelling.
The topics covered in the course will be the following
1. Basic concepts on network modelling
2. Different software appropriate to network modelling
3. How to find information necessary to construct metabolic and signal transduction network in the different existing databases
4. Experimental information necessary to construct a metabolic model
5. Metabolic models based on kinetic data
6. Robustness, and dynamic characterization of a metabolic model
7. Metabolic Control Analysis as a tool to characterize metabolic networks
8. Experimental information necessary to construct a signal transduction model
9. Deterministic and estocastic methods to model signal transduction pathways
10. How to include protein complexes and substrate channelling in metabolic and signal transduction models
11. The importance of construct models that can easily be exported and common platforms implemented in websites to make models easy to use by everybody
12. Examples of models that have resulted in useful biomedical or biotechnological purposes
Venue:
St Hughes College, in the University of Oxford, UK
September, 2004 (dates to be confirmed)
Participation:
Number of places available: 25
The course is aimed
at PhD students, in biomedical or biotechnological areas, who would like to
apply modelling tools to a problem relevant to/associated with their theses.
It is also applicable to researchers who would like to move to systems biology
research area and have found difficulties in updating their knowledge in the
existing tools and in starting to construct models from their experimental data.
Programme: (provisional)
Day 0: Saturday
19:00 Get together. Dinner.
Day 1: Sunday
9:00-9:30 Welcome and Introduction to the course
9:30-13:00 Lectures to introduce the students to the basic tools for modelling metabolic and signal transduction pathways and to the use of databases.
15.00-18:30 Half of the students will present a research project in which they are working or plan to work in which they would like to apply the modelling tools.
19.00-20.00 Organized discussion
Day 2: Tuesday
9:00-13:00 The other half of the students will present a research project in which they are working or plan to work in which they will like to apply the modelling tools.
14:30-19:00 Practical session in which the students will start to construct a simple model with the assistant of teachers
16:30-17:30 Open Public Lecture.
1900-20:00 Organized discussion.
Day 3: Wednesday
9:00-13:00 Open public lectures
14:30-16:30 Open public lecture
16:30 End of the course
Registration:
Registration is closed.