Grasping frequent subgraph mining for bioinformatics applications-Reference-Cited by-同舟云学术

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Grasping frequent subgraph mining for bioinformatics applications

Published:2018-09-03 Issue:1 Volume:11 Page:
ISSN:1756-0381
Container-title:BioData Mining
language:en
Short-container-title:BioData Mining

Author:

Mrzic Aida,Meysman Pieter,Bittremieux Wout,Moris Pieter,Cule Boris,Goethals Bart,Laukens Kris^ORCID

Funder

Fonds Wetenschappelijk Onderzoek

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Genetics,Molecular Biology,Biochemistry

Link

http://link.springer.com/content/pdf/10.1186/s13040-018-0181-9.pdf

Reference88 articles.

1. Koyutürk M, Grama A, Szpankowski W. An efficient algorithm for detecting frequent subgraphs in biological networks. Bioinformatics. 2004; 20(suppl 1):200–7.

2. Hu H, Yan X, Huang Y, Han J, Zhou XJ. Mining coherent dense subgraphs across massive biological networks for functional discovery. Bioinformatics. 2005; 21(suppl 1):213–21.

3. Cakmak A, Ozsoyoglu G. Mining biological networks for unknown pathways. Bioinformatics. 2007; 23(20):2775–83.

4. Meysman P, Zhou C, Cule B, Goethals B, Laukens K. Mining the entire protein databank for frequent spatially cohesive amino acid patterns. BioData Min. 2015; 8(1):1.

5. Jiang C, Coenen F, Zito M. A survey of frequent subgraph mining algorithms. Knowl Eng Rev. 2013; 28(01):75–105.

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