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タイトル: Grammar-based compression approach to extraction of common rules among multiple trees of glycans and RNAs.
著者: Zhao, Yang
Hayashida, Morihiro
Cao, Yue
Hwang, Jaewook
Akutsu, Tatsuya  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0001-9763-797X (unconfirmed)
著者名の別形: 林田, 守広
阿久津, 達也
キーワード: Grammar-based compression
Bisection-type tree grammar
Glycan
RNA secondary structure
発行日: 24-Apr-2015
出版者: BioMed Central Ltd.
誌名: BMC bioinformatics
巻: 16
論文番号: 128
抄録: [Background]Many tree structures are found in nature and organisms. Such trees are believed to be constructed on the basis of certain rules. We have previously developed grammar-based compression methods for ordered and unordered single trees, based on bisection-type tree grammars. Here, these methods find construction rules for one single tree. On the other hand, specified construction rules can be utilized to generate multiple similar trees. [Results]Therefore, in this paper, we develop novel methods to discover common rules for the construction of multiple distinct trees, by improving and extending the previous methods using integer programming. We apply our proposed methods to several sets of glycans and RNA secondary structures, which play important roles in cellular systems, and can be regarded as tree structures. The results suggest that our method can be successfully applied to determining the minimum grammar and several common rules among glycans and RNAs. [Conclusions]We propose integer programming-based methods MinSEOTGMul and MinSEUTGMul for the determination of the minimum grammars constructing multiple ordered and unordered trees, respectively. The proposed methods can provide clues for the determination of hierarchical structures contained in tree-structured biological data, beyond the extraction of frequent patterns.
著作権等: © Zhao et al.; licensee BioMed Central. 2015
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​4.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.
URI: http://hdl.handle.net/2433/210405
DOI(出版社版): 10.1186/s12859-015-0558-4
PubMed ID: 25907438
出現コレクション:学術雑誌掲載論文等

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