Quantifying the implicit process flow abstraction in SBGN-PD diagrams with Bio-PEPA

TL;DR

This paper formalizes the implicit process flow in SBGN-PD diagrams, enabling automated quantitative modeling with Bio-PEPA, demonstrated through biochemical network analysis like the MAPK cascade.

Contribution

It explicitly describes the process flow abstraction in SBGN-PD and develops a tool to generate Bio-PEPA models from textual representations.

Findings

Automated generation of Bio-PEPA code from SBGN-PD diagrams.

Quantitative analysis of biochemical networks using the developed scheme.

Demonstration of delay computation in MAPK cascade.

Abstract

For a long time biologists have used visual representations of biochemical networks to gain a quick overview of important structural properties. Recently SBGN, the Systems Biology Graphical Notation, has been developed to standardise the way in which such graphical maps are drawn in order to facilitate the exchange of information. Its qualitative Process Diagrams (SBGN-PD) are based on an implicit Process Flow Abstraction (PFA) that can also be used to construct quantitative representations, which can be used for automated analyses of the system. Here we explicitly describe the PFA that underpins SBGN-PD and define attributes for SBGN-PD glyphs that make it possible to capture the quantitative details of a biochemical reaction network. We implemented SBGNtext2BioPEPA, a tool that demonstrates how such quantitative details can be used to automatically generate working Bio-PEPA code from a textual representation of SBGN-PD that we developed. Bio-PEPA is a process algebra that was designed for implementing quantitative models of concurrent biochemical reaction systems. We use this approach to compute the expected delay between input and output using deterministic and stochastic simulations of the MAPK signal transduction cascade. The scheme developed here is general and can be easily adapted to other output formalisms.