Finding specific RNA sequence motifs using digital filters

Local distinct structural elements, called motifs, in RNA sequences are strictly correlated with their function. Due to the enormous increase of genomic data in recent times, highly effective computational algorithms are in greater demand for identification of such motifs in RNA sequences. In this w...

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Bibliographic Details
Published in2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) pp. 1 - 4
Main Authors Rajasekhar, K., Ahmad, M. O., Devabhaktuni, V.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2012
Subjects
Bioinformatics
DNA
Genomics
Proteins
Ribonucleic acid (RNA)
RNA
sequence motif
Signal to noise ratio
statistically optimal null filter
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ISBN1467314315
9781467314312
ISSN0840-7789
DOI10.1109/CCECE.2012.6335032

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Summary:Local distinct structural elements, called motifs, in RNA sequences are strictly correlated with their function. Due to the enormous increase of genomic data in recent times, highly effective computational algorithms are in greater demand for identification of such motifs in RNA sequences. In this work, a digital signal processing approach using statistically optimal null filter (SONF) is developed for finding specific motifs in an RNA sequence. The instantaneous matched filter in SONF determines the degree of local alignment between the motif and the windowed RNA sequence being compared. Through example the effectiveness of the proposed approach is illustrated. In particular, the proposed method is highly efficient in identifying similar motifs in large RNA sequences.
ISBN:1467314315
9781467314312
ISSN:0840-7789
DOI:10.1109/CCECE.2012.6335032