Systems biology is now an established and fundamental field in life sciences. It has facilitated the move from the identification of molecular ‘parts lists’ for living organisms towards integrating information from different ‘omics’-based approaches with our knowledge on the underlying biochemical mechanisms, to generate and test new hypotheses about how biological systems work. This joint EMBL-EBI-Wellcome Trust course will combine lectures on modelling approaches, led discussions to identify the key challenges, opportunities and bottlenecks, and practical sessions on network analysis and network-based modelling.
Please note: This course will not cover high-throughput ‘omics’ data analysis methods, e.g. statistical models, GWAS analysis, etc. We will touch on protein networks and data integration, but the focus is more on building predictive and mechanistic models. If you are interested in protein networks, please consider the Interaction and Pathways course instead.
Topics
• Overview of the field of Systems Biology: past, present and future
• Analysis of Gene Regulatory Networks
• Qualitative Modelling: modelling and simulation of interesting networks and pathways, as well as analysis of dynamical systems
• Quantitative Modelling: Chemical kinetics, constraint-based modelling and stochastic simulations
• Network and Pathway Enrichment
• Model sharing: how to encode and annotate models
• Programmatic approaches (e.g. libSBML)
Target audience
The course is aimed at advanced PhD students, post-doctoral and more senior researchers who are using or planning to use systems-based approaches to understand biomedical problems.
Please note: Previous experience in computational and/or systems biology approaches is required to attend this course.
After this course you should be able to…
- Know how the field of systems biology has developed
- Understand some of the challenges that we face in the field of systems biology today
- Develop your presentation skills
- Understand a range of approaches for modeling gene regulatory networks
- Learn approaches to build and explore protein-protein interactions networks
- Analyze and annotate interaction networks using Cytoscape and BiNGO
- Learn the standard formats used to express models in the life sciences
- Explore pathways using Cytoscape
- Analyze networks using R and GinSiM
- Learn general principles for chemical kinetic modeling
- Use simulation based approaches to model complex pathways using COPASI
- Understand some general principles of stochastic simulations
- Understand the terms ‘robustness’ and ‘sensitivity’ in the context of parameter estimation
- Understand some general principles of constraint based models and their implementation
- Learn the general principles, and gain hand-on experience of parameter estimation
- Learn about the structure and syntax of systems biology markup language (SBML) and relevant resources available
- Implement systems biology markup language with Python
- Access and explore the BioModels database
- Develop an awareness of the minimum controlled annotations for systems biology models (MIRIAM) guidelines
- Develop an awareness of a variety of other types of model including spatial models
Participants will be encouraged to bring their own data for one-to-one sessions. However, specific size limits and formats will be specified in order to ensure data is usable in the available time. Participants will also be requested to provide a poster for the poster session.
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