代谢与各种细胞过程紧密相连，包括控制细胞命运、影响肿瘤发生、参与应激反应等。代谢是一个复杂的、相互依赖的网络，局部扰动可能会对代谢网络产生普遍的间接影响。目前的分析和技术限制长期以来一直制约着代谢数据的解释。为了解决这些缺点，我们开发了Metaboverse，这是一个用户友好的工具，旨在促进数据探索和假设生成。我们在这里介绍算法，利用代谢网络从数据中提取复杂的反应模式。为了最小化网络中缺失测量的影响，我们介绍了一些方法，可以实现跨多个反应的模式识别。使用Metaboverse，我们确定了一种先前未描述的代谢物标志，与早期肺腺癌患者的生存结果相关。使用酵母模型，我们确定代谢反应，表明柠檬酸平衡在细胞质功能障碍、由柠檬酸转运蛋白Ctp1促进的线粒体功能障碍期间具有适应性作用。我们证明了Metaboverse增强了用户从多组学数据集中提取有意义模式并形成可操作假说的能力。©2023.作者。

Metabolism is intertwined with various cellular processes, including controlling cell fate, influencing tumorigenesis, participating in stress responses and more. Metabolism is a complex, interdependent network, and local perturbations can have indirect effects that are pervasive across the metabolic network. Current analytical and technical limitations have long created a bottleneck in metabolic data interpretation. To address these shortcomings, we developed Metaboverse, a user-friendly tool to facilitate data exploration and hypothesis generation. Here we introduce algorithms that leverage the metabolic network to extract complex reaction patterns from data. To minimize the impact of missing measurements within the network, we introduce methods that enable pattern recognition across multiple reactions. Using Metaboverse, we identify a previously undescribed metabolite signature that correlated with survival outcomes in early stage lung adenocarcinoma patients. Using a yeast model, we identify metabolic responses suggesting an adaptive role of citrate homeostasis during mitochondrial dysfunction facilitated by the citrate transporter, Ctp1. We demonstrate that Metaboverse augments the user's ability to extract meaningful patterns from multi-omics datasets to develop actionable hypotheses.© 2023. The Author(s).