Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach-Reference-Cited by-同舟云学术

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Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach

Published:2018-03 Issue:S2 Volume:12 Page:
ISSN:1752-0509
Container-title:BMC Systems Biology
language:en
Short-container-title:BMC Syst Biol

Author:

Peng Jiajie,Zhang Xuanshuo,Hui Weiwei,Lu Junya,Li Qianqian,Liu Shuhui,Shang Xuequn

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Modeling and Simulation,Structural Biology

Link

http://link.springer.com/content/pdf/10.1186/s12918-018-0539-0.pdf

Reference33 articles.

1. Consortium GO, et al. Expansion of the gene ontology knowledgebase and resources. Nucleic Acids Res. 2017; 45(D1):331–38.

2. Vafaee F, Rosu D, Broackes-Carter F, Jurisica I. Novel semantic similarity measure improves an integrative approach to predicting gene functional associations. BMC Syst Biol. 2013; 7(1):22.

3. Cheng L, Sun J, Xu W, Dong L, Hu Y, Zhou M. Oahg: an integrated resource for annotating human genes with multi-level ontologies. Sci Rep. 2016; 6:34820.

4. Peng J, Bai K, Shang X, Wang G, Xue H, Jin S, Cheng L, Wang Y, Chen J. Predicting disease-related genes using integrated biomedical networks. BMC Genomics. 2017; 18(1):1043.

5. Peng J, Wang T, Wang J, Wang Y, Chen J. Extending gene ontology with gene association networks. Bioinformatics. 2015; 32(8):1185–94.

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