Material Detail

Identifying interactions in the time and frequency domains in local and global networks

Identifying interactions in the time and frequency domains in local and global networks

This video was recorded at Learning and Inference in Computational Systems Biology (LICSB), Warwick 2010. Reverse-engineering approaches such as Bayesian network inference, ordinary differential equations (ODEs) and information theory are widely applied to deriving causal relationships among different elements such as genes, proteins, metabolites, neurons, brain areas and so on, based upon multi-dimensional spatial and temporal data. Here we focused on the Granger causality approach in both the time and frequency domains in local and global networks, and applied our approach to experimental data (genes and proteins). For a small gene network, Granger causality outperformed all the other three approaches mentioned above. A global protein network from 812 proteins was reconstructed, using a... Show More

Quality

  • User Rating
  • Comments
  • Learning Exercises
  • Bookmark Collections
  • Course ePortfolios
  • Accessibility Info

More about this material

Comments

Log in to participate in the discussions or sign up if you are not already a MERLOT member.