Logical Modeling for Experimental Design in Current and Future Biotechnology and Biomedicine
The course builds on approaches and technologies that we are currently developing in the NTNU DrugLogics initiative, where we use the logical modelling formalism for predicting the outcome of chemical perturbations (cancer drugs) on cancer cell fate decisions. 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.
Application deadline: 23 July
- Theoretical principles as well as existing tools and resources for logical modeling
- Resources and tools for knowledge management to underpin logical modeling
- Computational biology assisted reasoning for (large scale) hypothesis management by using logical modeling
- (Large scale) hypothesis management for interpretation of biotechnology-/biomedicine experimental data and for design of new experiments
- Fundamental challenges in future biotechnology and biomedicine that require logical modeling for adequate hypothesis management
- Discussion of trajectories for development of modeling-based research infrastructures for future biotechnology and biomedicine including reflections on implications of each of the trajectories for users and stakeholders of these infrastructures
If you are a member of Digital Life Norway Research School, all your costs related to course attendance can be covered if you apply for a travel grant.
Liv Eggset Falkenberg