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A detection method for snoRNA modification domain by fully indexable dictionary retrieving

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Abstract

Recently, non-coding RNA which participates with organic activities has been found in non-coding region. Until now, we do not know detailed function of non-coding RNAs very well. To make clear functions of non-coding RNAs, we need to obtain a lot of data about non-coding RNAs and their targets. However, we do not have efficient techniques to analyze relations between non-coding RNAs and their targets. In this paper, we propose a high-speed method that can detect modification domain candidates on the target RNA based on the small nucleolar RNA (snoRNA) sequence. A snoRNA modifies a target RNA by composing complementary base pairs between a part of snoRNA and a part of target RNA. Our method stores the relations between snoRNA sequences and their target in a Fully Indexable Dictionary built by Trie data structure and Level-Order Unary Degree Sequence for high-speed retrieving.

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Authors and Affiliations

  1. Faculty of Engineering, University of Miyazaki, 1-1 Gakuen Kibanadai Nishi, Miyazaki, 889-2192, Japan

    Takayuki Yamamoto, Kunihito Yamamori, Naoya Kenmochi & Masaru Aikawa

Authors
  1. Takayuki Yamamoto
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  2. Kunihito Yamamori
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  3. Naoya Kenmochi
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  4. Masaru Aikawa
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Corresponding author

Correspondence to Kunihito Yamamori.

Additional information

This work was presented in part at the 19th International Symposium on Artificial Life and Robotics, Beppu, Oita, January 22–24, 2014.

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Yamamoto, T., Yamamori, K., Kenmochi, N. et al. A detection method for snoRNA modification domain by fully indexable dictionary retrieving. Artif Life Robotics 19, 209–214 (2014). https://doi.org/10.1007/s10015-014-0149-x

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  • DOI: https://doi.org/10.1007/s10015-014-0149-x

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