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Exploring Essential Attributes for Detecting MicroRNA Precursors from Background Sequences
Author(s) -
Yun Zheng,
Wynne Hsu,
Mong Li Lee,
Limsoon Wong
Publication year - 2006
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-68970-2
DOI - 10.1007/11960669_12
Subject(s) - microrna , encode , computational biology , biology , phylogenetic tree , gene , biogenesis , genetics
MicroRNAs (miRNAs) have been shown to play important roles in post-transcriptional gene regulation. The hairpin structure is a key characteristic of the microRNAs precursors (pre-miRNAs). How to encode their hairpin structures is a critical step to correctly detect the pre-miRNAs from background sequences, i.e., pseudo miRNA precursors. In this paper, we have proposed to encode the hairpin structures of the pre-miRNA with a set of features, which captures both the global and local structure characteristics of the pre-miRNAs. Furthermore, we find that four essential attributes are discriminatory for classifying human pre-miRNAs and background sequences with an information theory approach. The experimental results show that the number of conserved essential attributes decreases when the phylogenetic distance between the species increases. Specifically, one A-U pair, which produces the U at the start position of most mature miRNAs, in the pre-miRNAs is found to be well conserved in different species for the purpose of biogenesis.

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