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PSSMTS: position specific scoring matrices on tree structures

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Abstract

Identifying non-coding RNA regions on the genome using computational methods is currently receiving a lot of attention. In general, it is essentially more difficult than the problem of detecting protein-coding genes because non-coding RNA regions have only weak statistical signals. On the other hand, most functional RNA families have conserved sequences and secondary structures which are characteristic of their molecular function in a cell. These are known as sequence motifs and consensus structures, respectively. In this paper, we propose an improved method which extends a pairwise structural alignment method for RNA sequences to handle position specific scoring matrices and hence to incorporate motifs into structural alignment of RNA sequences. To model sequence motifs, we employ position specific scoring matrices (PSSMs). Experimental results show that PSSMs enable us to find individual RNA families efficiently, especially if we have biological knowledge such as sequence motifs.

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Authors and Affiliations

  1. Japan Biological Informatics Consortium, 2–45 Aomi, Koto-ku, Tokyo, 135–8073, Japan

    Kengo Sato

  2. Department of Biosciences and Informatics, Keio University, 3–14–1 Hiyoshi, Kohoku-ku, Yokohama, 223–8522, Japan

    Kensuke Morita & Yasubumi Sakakibara

Authors
  1. Kengo Sato
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  2. Kensuke Morita
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  3. Yasubumi Sakakibara
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Corresponding author

Correspondence to Kengo Sato.

Additional information

K. Sato and K. Morita contributed equally to this work.

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Sato, K., Morita, K. & Sakakibara, Y. PSSMTS: position specific scoring matrices on tree structures. J. Math. Biol. 56, 201–214 (2008). https://doi.org/10.1007/s00285-007-0108-4

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  • DOI: https://doi.org/10.1007/s00285-007-0108-4

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