Here, we model the data structure based on 'observables' within systems biology studies to develop a library of 'motif's that may be composed together to represent the scientific observations generated within studies of cancer pathways.
This is concerned with our efforts to apply the KEfED methodology (http://www.kefed.org/) to the study of cancer pathways as part of the Big Mechanisms DARPA program. Here, we strive to apply this approach to systems biology, making it more agile and effective and supporting multiple activities including text mining and modeling efforts.
This website provides evolving, dynamic technical documentation for research work within the RUBICON group of the DARPA Big Mechanism project.
If you have any questions, feedback or issues concerning this work, contact us at gully@usc.edu.