PyGTED: Python']Python Application for Computing Graph Traversal Edit Distance

被引:0
|
作者
Boroojeny, Ali Ebrahimpour [1 ]
Shrestha, Akash [1 ]
Sharifi-zarchi, Ali [2 ]
Gallagher, Suzanne Renick [1 ]
Sahinalp, Suleyman Cenk [3 ]
Chitsaz, Hamidreza [1 ]
机构
[1] Colorado State Univ, Dept Comp Sci, 279 Comp Sci Bldg,1873 Campus Delivery, Ft Collins, CO 80523 USA
[2] Sharif Univ Technol, Dept Comp Engn, Tehran, Iran
[3] NCI, NIH, Bethesda, MD 20892 USA
关键词
clustering genera; coassembly; de novo variation detaction; graph comparison; graph kernel; linear programming;
D O I
10.1089/cmb.2019.0510
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Graph Traversal Edit Distance (GTED) is a measure of distance (or dissimilarity) between two graphs introduced. This measure is based on the minimum edit distance between two strings formed by the edge labels of respective Eulerian traversals of the two graphs. GTED was motivated by and provides the first mathematical formalism for sequence coassembly and de novo variation detection in bioinformatics. Many problems in applied machine learning deal with graphs (also called networks), including social networks, security, web data mining, protein function prediction, and genome informatics. The kernel paradigm beautifully decouples the learning algorithm from the underlying geometric space, which renders graph kernels important for the aforementioned applications. In this article, we introduce a tool, PyGTED to compute GTED. It implements the algorithm based on the polynomial time algorithm devised for it by the authors. Informally, the GTED is the minimum edit distance between two strings formed by the edge labels of respective Eulerian traversals of the two graphs.
引用
收藏
页码:436 / 439
页数:4
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