Measuring over-generalization in the minimal multiple generalizations of biosequences

Yen Kaow Ng; Hirotaka Ono; Takeshi Shinohara

Measuring over-generalization in the minimal multiple generalizations of biosequences

Yen Kaow Ng, Hirotaka Ono, Takeshi Shinohara

mathematics and information

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

We consider the problem of finding a set of patterns that best characterizes a set of strings. To this end, Arimura et. al. [3] considered the use of minimal multiple generalizations (mmg) for such characterizations. Given any sample set, the mmgs are, roughly speaking, the most (syntactically) specific set of languages containing the sample within a given class of languages. Takae et. al. [17] found the mmgs of the class of pattern languages [1] which includes so-called sort symbols to be fairly accurate as predictors for signal peptides. We first reproduce their results using updated data. Then, by using a measure for estimating the level of over-generalizations made by the mmgs, we show results that explain the high level of accuracies resulting from the use of sort symbols, and discuss how better results can be obtained. The measure that we suggests here can also be applied to other types of patterns, e.g. the PROSITE patterns [4].

Original language	English
Title of host publication	Discovery Science - 8th International Conference, DS 2005, Proceedings
Pages	176-188
Number of pages	13
Publication status	Published - Dec 1 2005
Event	8th International Conference on Discovery Science, DS 2005 - , Singapore Duration: Oct 8 2005 → Oct 11 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3735 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	8th International Conference on Discovery Science, DS 2005
Country	Singapore
Period	10/8/05 → 10/11/05

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

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Ng, Y. K., Ono, H., & Shinohara, T. (2005). Measuring over-generalization in the minimal multiple generalizations of biosequences. In Discovery Science - 8th International Conference, DS 2005, Proceedings (pp. 176-188). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3735 LNAI).

Measuring over-generalization in the minimal multiple generalizations of biosequences. / Ng, Yen Kaow; Ono, Hirotaka; Shinohara, Takeshi.

Discovery Science - 8th International Conference, DS 2005, Proceedings. 2005. p. 176-188 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3735 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ng, YK, Ono, H & Shinohara, T 2005, Measuring over-generalization in the minimal multiple generalizations of biosequences. in Discovery Science - 8th International Conference, DS 2005, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3735 LNAI, pp. 176-188, 8th International Conference on Discovery Science, DS 2005, Singapore, 10/8/05.

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