Danaci Hasan Fehmi, Cetin-Atalay Rengul, Atalay Volkan
† Department of Computer Engineering, Middle East Technical University, Ankara, Turkey.
‡ KanSiL, Cancer Systems Biology Laboratory, Graduate School of Informatics, Middle East Technical University, Ankara, Turkey.
J Bioinform Comput Biol. 2018 Aug;16(4):1850007. doi: 10.1142/S0219720018500075. Epub 2018 Mar 26.
Visualizing large-scale data produced by the high throughput experiments as a biological graph leads to better understanding and analysis. This study describes a customized force-directed layout algorithm, EClerize, for biological graphs that represent pathways in which the nodes are associated with Enzyme Commission (EC) attributes. The nodes with the same EC class numbers are treated as members of the same cluster. Positions of nodes are then determined based on both the biological similarity and the connection structure. EClerize minimizes the intra-cluster distance, that is the distance between the nodes of the same EC cluster and maximizes the inter-cluster distance, that is the distance between two distinct EC clusters. EClerize is tested on a number of biological pathways and the improvement brought in is presented with respect to the original algorithm. EClerize is available as a plug-in to Cytoscape ( http://apps.cytoscape.org/apps/eclerize ).
将高通量实验产生的大规模数据可视化为生物图有助于更好地理解和分析。本研究描述了一种针对生物图的定制力导向布局算法EClerize，该生物图表示节点与酶委员会（EC）属性相关联的通路。具有相同EC类编号的节点被视为同一簇的成员。然后根据生物相似性和连接结构确定节点的位置。EClerize最小化簇内距离，即同一EC簇中节点之间的距离，并最大化簇间距离，即两个不同EC簇之间的距离。EClerize在多个生物通路上进行了测试，并展示了相对于原始算法所带来的改进。EClerize可作为Cytoscape的插件使用（http://apps.cytoscape.org/apps/eclerize）。
