miRNA Pattern Discovery from Sequence Alignment


Xiaohan Sun, Junying Zhang, Journal of Information Processing Systems Vol. 13, No. 6, pp. 1527-1543, Dec. 2017  

https://doi.org/10.3745/JIPS.04.0051
Keywords: Deep Sequencing Data, miRNA, Pattern Discovery
Fulltext:

Abstract

MiRNA is a biological short sequence, which plays a crucial role in almost all important biological process. MiRNA patterns are common sequence segments of multiple mature miRNA sequences, and they are of significance in identifying miRNAs due to the functional implication in miRNA patterns. In the proposed approach, the primary miRNA patterns are produced from sequence alignment, and they are then cut into short segment miRNA patterns. From the segment miRNA patterns, the candidate miRNA patterns are selected based on estimated probability, and from which, the potential miRNA patterns are further selected according to the classification performance between authentic and artificial miRNA sequences. Three parameters are suggested that bi-nucleotides are employed to compute the estimated probability of segment miRNA patterns, and top 1% segment miRNA patterns of length four in the order of estimated probabilities are selected as potential miRNA patterns.


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Cite this article
[APA Style]
Sun, X. & Zhang, J. (2017). miRNA Pattern Discovery from Sequence Alignment. Journal of Information Processing Systems, 13(6), 1527-1543. DOI: 10.3745/JIPS.04.0051.

[IEEE Style]
X. Sun and J. Zhang, "miRNA Pattern Discovery from Sequence Alignment," Journal of Information Processing Systems, vol. 13, no. 6, pp. 1527-1543, 2017. DOI: 10.3745/JIPS.04.0051.

[ACM Style]
Xiaohan Sun and Junying Zhang. 2017. miRNA Pattern Discovery from Sequence Alignment. Journal of Information Processing Systems, 13, 6, (2017), 1527-1543. DOI: 10.3745/JIPS.04.0051.