The course builds on approaches and technologies that have been developed within the NTNU DrugLogics initiative (www.druglogics.eu), which use the logical modelling formalism for predicting the outcome of chemical perturbations (cancer drugs) on cancer cell fate decisions, and on inflammation-based diseases. This approach combines knowledge management, logical model construction and computational simulation with experimental assays and hypothesis testing for pre-clinical (biotechnological) drug development and clinical decision support. The course will exemplify how such approaches can be used in both the biotechnological and biomedical sectors such as pre-clinical drug discovery and repurposing, and clinical development of diagnosis and (combinatorial) treatment of cancer and other diseases. The students will practice the new acquired skills in a small team-based project.

The course content will focus on:

Themes

1. 1. Intro – Model-based Systems Biology.
   2. Logical modelling of cellular networks.
   3. GINsim and BioLQM: logical modelling tool and model analysis tutorial.
   4. Model building approaches (top-down, bottom-up), modelling resources.
   5. From molecular maps to logical models.
   6. Stochastic logical modelling.
   7. Multiscale logical modelling.
   8. CoLoMoTo electronic notebook tutorial.
   9. Reproducible science.
   10. Student teams and project challenge selection.

The PhD-version of the course (BI8040) gives 7,5 ECTS study points. Teaching and course material: The teaching and project part of the course will start August 15 and end August 26. We will provide a web link to relevant literature and web resources that the course will be based on. Some of the papers will constitute mandatory reading before the course starts. The course will consist of 12 lectures and 50 hours of team/project-based learning: Student exercises and project-based learning in multidisciplinary teams applying tools and resources for modeling-based hypothesis generation and management. Some ideas for modelling projects will be provided. In addition, students may want to design their own project based on other literature or their PhD project results. These project ideas should be sent to the teaching staff prior to the course. Students will present their ideas for projects at the start of the course.

Course schedule:

Day 1:  Introductory lectures, introduction to team-based learning-sessions

Day 2-5: Combination of lectures/TBL and supervised student group work with tools and resources

Day 6-7: Project-work: develop and characterise logical models, and their implications for knowledge discovery

Day 8: Introduction to RRI aspects of the work

Day 9: Project-work: develop and characterise logical models, and their implications for knowledge discovery

Day 10: Presentations.

The students will use an eNotebook for the project and reporting. Students write their individual reports after the course finishes, deadline for submitting the report:  7 September.  

Teachers include:

Martin Kuiper, Professor Systems Biology, IBI, NTNU

Denis Thieffry, Professor Systems Biology, Department of Biology, IBENS, Paris, France, and Guest Researcher at the Systems Biology group of IBI, NTNU

Astrid Lægreid, Professor Functional Genomics, IKOM, NTNU

Rune Nydal, Ass. Professor ethics of technology, IFR, NTNU

Åsmund Flobak, Associate Professor IKOM-NTNU, MD/Oncologist St Olavs

Anna Niarakis, Associate Professor Computational Systems Biology, at Univ Evry, University of Paris-Saclay  

Several additional guest lecturers will participate, either via Zoom or in the lecture room. The language of lectures and instructions is English.

Application Procedure (deadline 10 August 2022):

Applications, including a motivation letter and a CV should be sent by email to kuiper@ntnu.no. There is only a limited number of places left. Deadline for application is August 10. Students should have an MSc either in biotechnology, biology, biomedicine, or computational biology.