PATHLOGIC-S: A scalable boolean framework for modelling cellular signalling

Fearnley, Liam G. and Nielsen, Lars K. (2012) PATHLOGIC-S: A scalable boolean framework for modelling cellular signalling. PLoS One, 7 8 Article. No.e41977: . doi:10.1371/journal.pone.0041977

Author Fearnley, Liam G.
Nielsen, Lars K.
Title PATHLOGIC-S: A scalable boolean framework for modelling cellular signalling
Journal name PLoS One   Check publisher's open access policy
ISSN 1932-6203
Publication date 2012-08-01
Year available 2012
Sub-type Article (original research)
DOI 10.1371/journal.pone.0041977
Open Access Status DOI
Volume 7
Issue 8 Article. No.e41977
Total pages 9
Place of publication San Francisco, CA United States
Publisher Public Library of Science
Language eng
Formatted 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.
Keyword Functional-Analysis
Androgen Receptor
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID DP110103384
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
Australian Institute for Bioengineering and Nanotechnology Publications
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