Automated visualization of rule-based models

Frameworks such as BioNetGen, Kappa and Simmune use “reaction rules” to specify biochemical interactions compactly, where each rule specifies a mechanism such as binding or phosphorylation and its structural requirements. Current rule-based models of signaling pathways have tens to hundreds of rules, and these numbers are expected to increase as more molecule types and pathways are added. Visual representations are critical for conveying rule-based models, but current approaches to show rules and interactions between rules scale poorly with model size. Also, inferring design motifs that emerge from biochemical interactions is an open problem, so current approaches to visualize model architecture rely on manual interpretation of the model. Here, we present three new visualization tools that constitute an automated visualization framework for rule-based models: (i) a compact rule visualization that efficiently displays each rule, (ii) the atom-rule graph that conveys regulatory interactions in the model as a bipartite network, and (iii) a tunable compression pipeline that incorporates expert knowledge and produces compact diagrams of model architecture when applied to the atom-rule graph. The compressed graphs convey network motifs and architectural features useful for understanding both small and large rule-based models, as we show by application to specific examples. Our tools also produce more readable diagrams than current approaches, as we show by comparing visualizations of 27 published models using standard graph metrics. We provide an implementation in the open source and freely available BioNetGen framework, but the underlying methods are general and can be applied to rule-based models from the Kappa and Simmune frameworks also. We expect that these tools will promote communication and analysis of rule-based models and their eventual integration into comprehensive whole-cell models.

诸如BioNetGen、Kappa与Simmune这类生化建模框架，均借助反应规则（reaction rules）以紧凑形式定义生化相互作用；每条规则会阐明结合、磷酸化等作用机制及其对应的结构要求。当前基于规则的信号通路模型通常包含数十至数百条规则，且随着更多分子类型与通路被纳入，规则数量预计还将进一步增长。可视化表征对于传递基于规则的模型核心信息至关重要，但现有展示规则及规则间相互作用的方法，在模型规模扩大时可扩展性不佳。此外，从生化相互作用中推导涌现出的设计基序（design motifs）仍是尚未解决的开放性问题，因此当前可视化模型架构的方法均依赖于研究人员对模型的人工解读。本研究提出三种全新可视化工具，共同构成面向基于规则模型的自动化可视化框架：(i) 紧凑规则可视化模块，可高效展示单条规则；(ii) 原子-规则图（atom-rule graph），以二分网络形式呈现模型中的调控相互作用；(iii) 可调式压缩流水线，可融合专家领域知识，在应用于原子-规则图时可生成简洁直观的模型架构示意图。正如我们在具体示例中展示的那样，经压缩的图可清晰呈现网络基序与架构特征，有助于理解不同规模的基于规则模型。通过采用标准图度量指标对比27个已发表模型的可视化结果，我们证实本工具生成的示意图相较于现有方法更具可读性。我们已在开源且可免费获取的BioNetGen框架中实现了该工具集，但核心方法具备普适性，同样可应用于Kappa与Simmune框架下的基于规则模型。我们期望这些工具能够推动基于规则模型的学术交流与分析工作，并最终助力其整合至完整的全细胞模型中。