Using RuleBuilder to graphically define and visualize BioNetGen-language patterns and reaction rules

TL;DR

RuleBuilder is a graphical tool that simplifies creating, visualizing, and interpreting BioNetGen language models for biochemical systems by converting between graphical and string representations.

Contribution

It introduces a user-friendly interface for constructing and understanding BNGL models, enhancing readability and model development efficiency.

Findings

Enables conversion of BNGL strings to graph representations.

Allows graphical construction of BNGL models with real-time string generation.

Facilitates easier reading and writing of complex biochemical reaction rules.

Abstract

RuleBuilder is a tool for drawing graphs that can be represented by the BioNetGen language (BNGL), which is used to formulate mathematical, rule-based models of biochemical systems. BNGL provides an intuitive plain-text, or string, representation of such systems, which is based on a graphical formalism. Reactions are defined in terms of graph-rewriting rules that specify the necessary intrinsic properties of the reactants, a transformation, and a rate law. Rules may also contain contextual constraints that restrict application of the rule. In some cases, the specification of contextual constraints can be verbose, making a rule difficult to read. RuleBuilder is designed to ease the task of reading and writing individual reaction rules, as well as individual BNGL patterns similar to those found in rules. The software assists in the reading of existing models by converting BNGL strings of interest into a graph-based representation composed of nodes and edges. RuleBuilder also enables the user to construct de novo a visual representation of BNGL strings using drawing tools available in its interface. As objects are added to the drawing canvas, the corresponding BNGL string is generated on the fly, and objects are similarly drawn on the fly as BNGL strings are entered into the application. RuleBuilder thus facilitates construction and interpretation of rule-based models.