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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.