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OJBTM

Online Journal of Bioinformatics

Volume 22 (2): 96-111, 2021.


Web tool for classification and prediction of ribonucleases

 

Bhasker Pant1, KR Pardasani2

 

1Department (s) Bioinformatics, 2Mathematics, MANIT, Bhopal, India.

ABSTRACT

 

Bhasker P, Pardasani KR., Web tool for classification and prediction of ribonucleases, Onl J Bioinform., 22 (2): 96-111, 2021. Ribonuclease [RNase] catalyzes RNA into endoribonucleases and exoribonucleases. Organisms have different classes of RNases involved with cancers and neuro degenerative disorders and their classification and function prediction would be useful for drug design. Machine learning has been used to classify GPCRs proteins but not for ribonucleases. We developed a support vector machine (SVM) to predict, classify and correlate the major subclasses of ribonucleases with their dipeptide composition. The method was tested on 1857 ribonuclease proteins to discriminate them from other enzymes yielding Matthew's correlation coefficient of 1.00 and 100% accuracy. By classifying ribonucleases with dipeptide composition, we achieved ~94% accuracy. Performance was confirmed by 5-fold cross-validation. A web server DiRiboPred was then built to predict ribonucleases from its amino acid sequence.

 

Keywords: Classifier, Dipeptide Composition, Ribonucleases, Support Vector Machine.


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