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OJBTM
Online Journal of Bioinformatics©
Volume 21(2): 97-105, 2020..
A support
vector machine for classification of plant and animal miRNA.
KR Pardasani1,
Bhasker Pant2, Kumud
Pant2.
Department(s) of 1Mathematics, 2Bioinformatics,
MANIT, Bhopal, India.
ABSTRACT
Pardasani KR, Pant B, Pant K.,
Support vector machine for classification of plants and animal miRNA, Onl J Bioinform., 21(2): 97-105, 2020.. MicroRNAs (miRNAs) constitute a large family of
non-coding RNAs that function to regulate gene expression. Wet lab experiments
used to classify miRNA of plants and animals are expensive, labor intensive and
time consuming. Thus there arises a need for computational approach for
classification of plants and animal miRNA. These computational approaches are
fast and economical compared with wet lab techniques. We developed a support vector machine (SVM)
learning Sequential Minimal Optimization (or SMO) algorithm
for classification of plant and animal miRNA. The number of mismatches with
target mRNA, presence of clusters, number of target genes and size of fold back
loop used in the SVM model gave us 97% accuracy suggesting that these four
characteristics must be included in any classifier of plant and animal miRNA’s.
Key-words: Support vector, classification, miRNA.
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