Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/40946
Title: Exploring essential attributes for detecting MicroRNA Precursors from background sequences
Authors: Zheng, Y. 
Hsu, W. 
Lee, M.L. 
Wong, L. 
Issue Date: 2006
Source: Zheng, Y.,Hsu, W.,Lee, M.L.,Wong, L. (2006). Exploring essential attributes for detecting MicroRNA Precursors from background sequences. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4316 LNBI : 131-145. ScholarBank@NUS Repository.
Abstract: 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. © Springer-Verlag Berlin Heidelberg 2006.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/40946
ISBN: 3540689702
ISSN: 03029743
Appears in Collections:Staff Publications

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