Chanumolu Sree K, Albahrani Mustafa, Can Handan, Otu Hasan H
Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE, United States.
EMBnet J. 2021;26. doi: 10.14806/ej.26.0.949. Epub 2021 Mar 5.
The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database provides a manual curation of biological pathways that involve genes (or gene products), metabolites, chemical compounds, maps, and other entries. However, most applications and datasets involved in omics are gene or protein-centric requiring pathway representations that include direct and indirect interactions only between genes. Furthermore, special methodologies, such as Bayesian networks require acyclic representations of graphs. We developed KEGG2Net, a web resource that generates a network involving only the genes represented on a KEGG pathway with all of the direct and indirect gene-gene interactions deduced from the pathway. KEGG2Net offers four different methods to remove cycles from the resulting gene interaction network, converting them into directed acyclic graphs (DAGs). We generated synthetic gene expression data using the gene interaction networks deduced from the KEGG pathways and performed a comparative analysis of different cycle removal methods by testing the fitness of their DAGs to the data and by the number of edges they eliminate. Our results indicate that an ensemble method for cycle removal performs as the best approach to convert the gene interaction networks into DAGs. Resulting gene interaction networks and DAGs are represented in multiple user-friendly formats that can be used in other applications, and as images for quick and easy visualisation. The KEGG2Net web portal converts KEGG maps for any organism into gene-gene interaction networks and corresponding DAGS representing all of the direct and indirect interactions among the genes.
京都基因与基因组百科全书（KEGG）通路数据库提供了对生物通路的人工整理，这些通路涉及基因（或基因产物）、代谢物、化合物、图谱及其他条目。然而，大多数组学相关的应用和数据集是以基因或蛋白质为中心的，这就需要通路表示仅包括基因之间的直接和间接相互作用。此外，特殊方法（如贝叶斯网络）需要图的无环表示。我们开发了KEGG2Net，这是一个网络资源，它能生成一个仅包含KEGG通路中所代表基因的网络，并从该通路推导出所有直接和间接的基因-基因相互作用。KEGG2Net提供了四种不同方法来消除所得基因相互作用网络中的环，将其转换为有向无环图（DAG）。我们使用从KEGG通路推导出的基因相互作用网络生成了合成基因表达数据，并通过测试其DAG对数据的拟合度以及它们消除的边数，对不同的环消除方法进行了比较分析。我们的结果表明，一种环消除的集成方法是将基因相互作用网络转换为DAG的最佳方法。所得的基因相互作用网络和DAG以多种用户友好的格式表示，可用于其他应用，也可作为图像进行快速简便的可视化。KEGG2Net网站门户将任何生物体的KEGG图谱转换为基因-基因相互作用网络以及代表基因间所有直接和间接相互作用的相应DAG。
