Item type |
デフォルトアイテムタイプ(フル)(1) |
公開日 |
2020-12-16 |
タイトル |
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タイトル |
Rule-based Assembly for Short-read Datasets Obtained with Multiple Assemblers and k-mer Sizes |
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言語 |
en |
作成者 |
Ohshiro, Ayako
Afuso, Hitoshi
Okazaki, Takeo
Nakamura, Morikazu
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アクセス権 |
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アクセス権 |
open access |
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アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
権利情報 |
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言語 |
ja |
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権利情報 |
© 2017 by the Information Processing Society of Japan |
主題 |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
DNA assembly |
主題 |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
k-mer |
主題 |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
hybrid assembly |
主題 |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
decision tree |
主題 |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
C4.5 |
内容記述 |
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内容記述タイプ |
Other |
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内容記述 |
Various de novo assembly methods based on the concept of k-mer have been proposed. Despite the success of these methods, an alternative approach, referred to as the hybrid approach, has recently been proposed that combines different traditional methods to effectively exploit each of their properties in an integrated manner. However, the results obtained from the traditional methods used in the hybrid approach depend not only on the specific algorithm or heuristics but also on the selection of a user-specific k-mer size. Consequently, the results obtained with the hybrid approach also depend on these factors. Here, we designed a new assembly approach, referred to as the rule-based assembly. This approach follows a similar strategy to the hybrid approach, but employs specific rules learned from certain characteristics of draft contigs to remove any erroneous contigs and then merges them. To construct the most effective rules for this purpose, a learning method based on decision trees, i.e., a complex decision tree, is proposed. Comparative experiments were also conducted to validate the method. The results showed that proposed method could outperformed traditional methods in certain cases. |
内容記述 |
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内容記述タイプ |
Other |
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内容記述 |
論文 |
出版者 |
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出版者 |
Information Processing Society of Japan (IPSJ) |
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言語 |
en |
出版者 |
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出版者 |
情報処理学会 |
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言語 |
ja |
言語 |
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言語 |
eng |
資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
出版タイプ |
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出版タイプ |
VoR |
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出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
識別子 |
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識別子 |
http://hdl.handle.net/20.500.12000/47510 |
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識別子タイプ |
HDL |
関連情報 |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.2197/ipsjtbio.10.9 |
関連情報 |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.2197/ipsjtbio.10.9 |
収録物識別子 |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
1882-6679 |
収録物名 |
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収録物名 |
IPSJ Transactions on Bioinformatics |
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言語 |
en |
書誌情報 |
巻 10,
p. 9-15,
発行日 2017
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