title: PATHLOGIC-S: a scalable Boolean framework for modelling cellular signalling.
abstract: Curated databases of signal transduction have grown to describe several thousand reactions, and efficient use of these data requires the development of modelling tools to elucidate and explore system properties. We present PATHLOGIC-S, a Boolean specification for a signalling model, with its associated GPL-licensed implementation using integer programming techniques. The PATHLOGIC-S specification has been designed to function on current desktop workstations, and is capable of providing analyses on some of the largest currently available datasets through use of Boolean modelling techniques to generate predictions of stable and semi-stable network states from data in community file formats. PATHLOGIC-S also addresses major problems associated with the presence and modelling of inhibition in Boolean systems, and reduces logical incoherence due to common inhibitory mechanisms in signalling systems. We apply this approach to signal transduction networks including Reactome and two pathways from the Panther Pathways database, and present the results of computations on each along with a discussion of execution time. A software implementation of the framework and model is freely available under a GPL license.
authors.affiliation: Australian Institute of Bioengineering and Nanotechnology, University of Queensland, Brisbane, Queensland, Australia.
authors.forename: Liam G
authors.initials: LG
authors.lastname: Fearnley
authors.forename: Lars K
authors.initials: LK
authors.lastname: Nielsen
mesh_terms: D002477:Cells / Q000378:metabolism*; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D015203:Reproducibility of Results; D015398:Signal Transduction; D012984:Software; D049490:Systems Biology / Q000379:methods*