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Motivation

Towards a graphical rule editor for the Pathway Logic Assistant Amna Abbas 1 Carolyn Talcott 2 Merrill Knapp 2 Oliver Ray 1 1 University of Bristol, UK 2 SRI International, USA LDSSB’12, Bristol, UK 24 th September 2012. Motivation.

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Motivation

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  1. Towards a graphical rule editor for the Pathway Logic AssistantAmnaAbbas1 Carolyn Talcott2Merrill Knapp 2Oliver Ray 11University of Bristol, UK2SRI International, USALDSSB’12, Bristol, UK24th September 2012

  2. Motivation • “Symbolic Systems Biology is the qualitative and quantitative study of biological processes as integrated systems rather than isolated parts.” • ... • “The aim is to develop formal models that are as close as possible to domain experts (biologists) mental models.” • P. Lincoln and C. Talcott • in M.S.Iyengar(ed.) Symbolic Systems Biology: Theory and Methods • Jones and Bartlett, 2010, p.2

  3. Background • Pathway Logic • symbolic approach for reasoning about biological entities and processes • based on a rewriting logic system (Maude) • developed at SRI International (Lincoln, Talcott) • pl.csl.sri.com • Pathway Logic Assistant • tool for browsing and analysing pathway logic models • applied to large signalling and metabolic networks

  4. Background • Representation • entities (metabolites, species, genes, ...) • reactions (substrates, products, modifiers) • Reasoning • static analysis • forward simulation • forward search • backward search • model checking • constraint solving • meta-analysis

  5. Example: Maude Definition • this is what the biologists at SRI actually work with !

  6. Example: Maude Definition • this is what the biologists at SRI actually work with ! • substrates • products • modifiers

  7. Example: Petri net representation • even when rules are displayed graphically they are still hard to understand !

  8. Example: Petri net representation • even when rules are displayed graphically they are still hard to understand ! • complex formation • species location • species modification

  9. Introducing Our Graphical Rule Editor • our graphical interface should make editing and understanding rules easier !

  10. Introducing Our Graphical Rule Editor • our graphical interface should make editing and understanding rules easier ! • “right brain” vs. “left brain” (spatial representation of locations, complexes) • biologists “think in” cartoons (and actually write them down as before/after) • link formal representation to intuitive model

  11. Conclusion • Biologists should not need special training in logic to use symbolic systems biology tools • We have focused on providing intuitive graphical support for simple rule editing (making modifications, locations, and the before and after states more intuitive) • But the greater challenge is to provide interactive graphical feedback for complex modes of logical inference (input queries and output results).

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