Gene expression is regulated by a large variety of mechanisms. Previous studies attempting to model the quantitative relationships between gene expression levels and regulatory mechanisms have considered only one or a few mechanisms at a time, which cannot provide a full picture of the complex interactions among different mechanisms. This was partially due to the heterogeneity of the mechanisms, which involve different types of biological objects and data representations, making it hard to study them in a unified way. Here, we describe a flexible framework that can integrate very different types of data for studying their joint effects on gene expression. In this framework, domain knowledge is represented by metapaths, while the manifestations of their effects in actual data are summarized by an embedding of the biological objects in a latent space. We demonstrate the use of our framework in integrating several diverse types of data that are related to gene expression in different ways, including DNA contacts in three-dimensional genome architecture, protein–protein interactions, genomic neighbourhoods and broad chromatin accessibility domains. The modelling results reveal that these several types of data are able to model gene expression fairly well individually, but even better when integrated.

基因表达受多种机制调控。以前的尝试对基因表达水平和调节机制之间的定量关系进行建模的研究一次只考虑了一种或几种机制，而这无法提供不同机制之间复杂相互作用的完整描述。部分原因是机制的异质性，涉及不同类型的生物对象和数据表示形式，因此很难以统一的方式进行研究。在这里，我们描述了一个灵活的框架，该框架可以集成非常不同类型的数据，以研究它们对基因表达的联合影响。在此框架中，领域知识由元路径表示，而其效果在实际数据中的体现则是通过将生物物体嵌入潜在空间中来总结的。我们证明了我们框架的使用，以多种方式整合了与基因表达相关的多种不同类型的数据，包括三维基因组架构中的DNA接触，蛋白质-蛋白质相互作用，基因组邻域和广泛的染色质可及性域。建模结果表明，这几种类型的数据能够很好地对基因表达进行单独建模，但整合后甚至更好。基因组邻域和广泛的染色质可及性域。建模结果表明，这几种类型的数据能够很好地对基因表达进行单独建模，但整合后甚至更好。基因组邻域和广泛的染色质可及性域。建模结果表明，这几种类型的数据能够很好地对基因表达进行单独建模，但整合后甚至更好。