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Online Journal of Bioinformatics

Established 1995

ISSN  1443-2250

19(3):222-233, 2018.



DiRiboPred: A Web Tool For Classification and Prediction of Ribonucleases 


Bhasker Pant1, KR Pardasani2.


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



Pant B, Pardasani KR. DiRiboPred: A Web Tool For Classification and Prediction of Ribonucleases , Onl J Bioinform., 19(3):222-233, 2018. Ribonuclease [commonly abbreviated RNase] is a type of nuclease that catalyzes the degradation of RNA into smaller components and can be divided into endoribonucleases and exoribonucleases. All organisms studied contain many RNases of many different classes, showing that RNA degradation is a very ancient and important process. They are shown to have an important role in cancer, tumor and many neuro degenarative disorders for controlling which, in-silico drug designing can be a valuable tool. In the past machine learning has been used to classify other proteins like GPCRs but no attempt has been made for classification of Ribonucleases. Realizing their importance here an attempt has been made to develop an SVM model to predict, classify and correlate all the major subclasses of ribonucleases with their dipeptide composition. The method was trained and tested on 1857 proteins of ribonucleases. The method discriminated Ribonucleases from other enzymes with Matthew's correlation coefficient of 1.00 and 100% accuracy. In classifying different subclasses of Ribonucleases with dipeptide composition, an overall accuracy of 94.534% was achieved. The performance of the method was evaluated using 5-fold cross-validation. A web server DiRiboPred has been developed for predicting Ribonucleases from its amino acid sequence.


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