Palmer-Rodríguez Pere, Alberich Ricardo, Reyes-Prieto Mariana, Castro José A, Llabrés Mercè
Mathematics and Computer Science Department, University of the Balearic Islands, Ctra Valldemossa, Km 7.5, Palma, 07122, Balearic Islands, Spain.
Sequencing and Bioinformatics Service, Foundation for the Promotion of Health and Biomedical Research of the Valencian Community (FISABIO), Avda. de Catalunya, 21, 46020, Valencia, Valencia, Spain.
BMC Bioinformatics. 2025 Jan 28;26(1):31. doi: 10.1186/s12859-025-06048-w.
MetaDAG is a web-based tool developed to address challenges posed by big data from omics technologies, particularly in metabolic network reconstruction and analysis. The tool is capable of constructing metabolic networks for specific organisms, sets of organisms, reactions, enzymes, or KEGG Orthology (KO) identifiers. By retrieving data from the KEGG database, MetaDAG helps users visualize and analyze complex metabolic interactions efficiently.
MetaDAG computes two models: a reaction graph and a metabolic directed acyclic graph (m-DAG). The reaction graph represents reactions as nodes and metabolite flow between them as edges. The m-DAG simplifies the reaction graph by collapsing strongly connected components, significantly reducing the number of nodes while maintaining connectivity. MetaDAG can generate metabolic networks from various inputs, including KEGG organisms or custom data (e.g., reactions, enzymes, KOs). The tool displays these models on an interactive web page and provides downloadable files, including network visualizations. MetaDAG was tested using two datasets. In an eukaryotic analysis, it successfully classified organisms from the KEGG database at the kingdom and phylum levels. In a microbiome study, MetaDAG accurately distinguished between Western and Korean diets and categorized individuals by weight loss outcomes based on dietary interventions.
MetaDAG offers an effective and versatile solution for metabolic network reconstruction from diverse data sources, enabling large-scale biological comparisons. Its ability to generate synthetic metabolisms and its broad application, from taxonomy classification to diet analysis, make it a valuable tool for biological research. MetaDAG is available online, with user support provided via a comprehensive guide. MetaDAG: https://bioinfo.uib.es/metadag/ User guide: https://biocom-uib.github.io/MetaDag/.
MetaDAG是一个基于网络的工具，旨在应对组学技术产生的大数据带来的挑战，特别是在代谢网络重建和分析方面。该工具能够为特定生物体、生物体集合、反应、酶或KEGG直系同源物（KO）标识符构建代谢网络。通过从KEGG数据库检索数据，MetaDAG帮助用户高效地可视化和分析复杂的代谢相互作用。
MetaDAG计算两种模型：反应图和代谢有向无环图（m-DAG）。反应图将反应表示为节点，将它们之间的代谢物流动表示为边。m-DAG通过合并强连通分量简化反应图，在保持连通性的同时显著减少节点数量。MetaDAG可以从各种输入生成代谢网络，包括KEGG生物体或自定义数据（例如反应、酶、KO）。该工具在交互式网页上显示这些模型，并提供可下载文件，包括网络可视化。使用两个数据集对MetaDAG进行了测试。在真核生物分析中，它成功地在界和门水平对KEGG数据库中的生物体进行了分类。在一项微生物组研究中，MetaDAG准确地区分了西方饮食和韩国饮食，并根据饮食干预措施按减肥结果对个体进行了分类。
MetaDAG为从不同数据源进行代谢网络重建提供了一种有效且通用的解决方案，能够进行大规模生物比较。它生成合成代谢的能力及其广泛的应用，从分类学分类到饮食分析，使其成为生物学研究的宝贵工具。MetaDAG可在线获取，并通过全面指南提供用户支持手册。MetaDAG网址：https://bioinfo.uib.es/metadag/ 用户指南网址：https://biocom-uib.github.io/MetaDag/ 。
