A Survey of Graph Mining Techniques for Biological Datasets-Reference-Cited by-同舟云学术

A Survey of Graph Mining Techniques for Biological Datasets

Published:2010 Issue: Volume: Page:547-580
ISSN:1386-2944
Container-title:Managing and Mining Graph Data
language:
Short-container-title:

Author:

Parthasarathy S.,Tatikonda S.,Ucar D.

Publisher

Springer US

Link

http://link.springer.com/content/pdf/10.1007/978-1-4419-6045-0_18.pdf

Reference120 articles.

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3. Aoki, K., Ueda, N., Yamaguchi, A., Kanehisa, M., Akutsu, T., and Mamitsuka, H. (2004a). Application of a new probabilistic model for recognizing complex patterns in glycans.

4. Aoki, K., Yamaguchi, A., Okuno, Y., Akutsu, T., Ueda, N., Kanehisa, M., and Mamitsuka, H. (2003). Efficient tree-matching methods for accurate carbohydrate database queries. Genome Informatics Sl, pages 134–143.

5. Aoki, K., Yamaguchi, A., Ueda, N., Akutsu, T., Mamitsuka, H., Goto, S., and Kanehisa, M. (2004b). KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains. Nucleic acids research, 32(Web Server Issue):W267.

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