Methodological Approaches

The techniques used by COMBINE fellows and faculty are organized into four primary methodologies:

  • Network Measures: Which network measures capture important features in biological systems? What algorithms are needed to efficiently compute appropriate network measures for very large datasets? Experts: Michelle Girvan, Sridhar Hannenhalli, Mihai Pop.
  • Network Models: How do we model information cascades in biological networks? What network structures help confer dynamical stability? Experts: Ed Ott, Jim Yorke, Michelle Girvan, Raj Roy, Bill Fagan.
  • Network Statistics and Machine Learning: How can we infer network interactions in biological systems from noisy data? How do we adapt machine learning methods for inference problems specific to biological applications? Experts: Hector Corrada Bravo, Joseph JaJa, Amitabh Varshney, Wolfgang Losert.
  • Big Data Visualization: What are the best high-performance computing approaches for the visualization of large interaction datasets? How can we develop automated approaches for the visual exploration of complex networks? Experts: Amitabh Varshney, Joseph JaJa, Patrick Kanold.

Learn more about COMBINE’s research Application areas.