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CytoASP: a Cytoscape app for qualitative consistency reasoning, prediction and repair in biological networks

Kittas, Aristotelis ; Barozet, Amélie ; Sereshti, Jekaterina ; Grabe, Niels ; Tsoka, Sophia

In: BMC Systems Biology, 9 (2015), Nr. 34. pp. 1-7. ISSN 1752-0509

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Download (1MB) | Lizenz: Creative Commons LizenzvertragCytoASP: a Cytoscape app for qualitative consistency reasoning, prediction and repair in biological networks by Kittas, Aristotelis ; Barozet, Amélie ; Sereshti, Jekaterina ; Grabe, Niels ; Tsoka, Sophia underlies the terms of Creative Commons Attribution 3.0 Germany

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Abstract

Background: Qualitative reasoning frameworks, such as the Sign Consistency Model (SCM), enable modelling regulatory networks to check whether observed behaviour can be explained or if unobserved behaviour can be predicted. The BioASP software collection offers ideal tools for such analyses. Additionally, the Cytoscape platform can offer extensive functionality and visualisation capabilities. However, specialist programming knowledge is required to use BioASP and no methods exist to integrate both of these software platforms effectively. Results: We report the implementation of CytoASP, an app that allows the use of BioASP for influence graph consistency checking, prediction and repair operations through Cytoscape. While offering inherent benefits over traditional approaches using BioASP, it provides additional advantages such as customised visualisation of predictions and repairs, as well as the ability to analyse multiple networks in parallel, exploiting multi-core architecture. We demonstrate its usage in a case study of a yeast genetic network, and highlight its capabilities in reasoning over regulatory networks. Conclusion: We have presented a user-friendly Cytoscape app for the analysis of regulatory networks using BioASP. It allows easy integration of qualitative modelling, combining the functionality of BioASP with the visualisation and processing capability in Cytoscape, and thereby greatly simplifying qualitative network modelling, promoting its use in relevant projects.

Item Type: Article
Journal or Publication Title: BMC Systems Biology
Volume: 9
Number: 34
Publisher: BioMed Central
Place of Publication: London
Date Deposited: 08 Jan 2016 13:53
Date: 2015
ISSN: 1752-0509
Page Range: pp. 1-7
Faculties / Institutes: Medizinische Fakultät Heidelberg > Institut für Medizinische Biometrie und Informatik
Subjects: 570 Life sciences
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