Bringing Genomes To Life - Reconstruction and application of genome-scale networks
Metabolic reconstructions are a common denominator in systems biology. They represent biochemically, genetically and genomically structured knowledge-bases that capture current knowledge about an organism. Laboratories around the world are reconstructing metabolic networks for their organisms of interest, thus, there is an increasing need of researchers being familiar with the reconstruction process.
These metabolic networks can be readily converted into mathematical models and then used to investigate the genotype-phenotype relationship. This course will teach the reconstruction process and different modeling techniques employed in these areas. Recently, approaches have been developed to investigate dynamics states of genome-scale metabolic networks. Basics methods are introduced in the course. The following five modules will be covered during the course:
- High-throughput data types
- Reconstruction and model formulation
- Topological and steady state analysis
- Analysis of dynamic states
- Optional Module: Primer on Linear Algebra and Matlab
The course targets PhD students and post-docs from various scientific backgrounds. In particular, the course is oriented towards students interested in interdisciplinary research spanning biology, mathematics, and computer science.
Knowledge in these three areas is not required since the course teaches the necessary background and basic principles.