2022

Permanent URI for this collection

https://escholar.umt.edu.pk/handle/123456789/9628

Browse

Browsing 2022 by Author "Anam Umera"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    An intelligent model for the prediction of PIWI-interacting RNAs and their functions
    (UMT, Lahore, 2022) Anam Umera
    A documented class of short non-coding RNA molecules is known as PIWI interacting RNA (Pi RNA). The creation of new drugs and the identification of various tumor types are linked to the Pi RNA molecules. Additionally, it is related to controlling transcription of genes, squelching transposons, and preserving genomic stability. The discovery of pi RNAs and their functionality has grown to be a significant research topic in bioinformatics as a result of the crucial influence that pi RNAs play in bio. The 2L-PiRNA-ML predictor, is a strong two-layer predictor that is suggested in this research to enhance the prediction of PiRNA and their functionality. The suggested model uses Quadratic Discriminant Analysis Classifier, Linear Discriminant Analysis, Passive Aggressive Classifier, Gradient Boosting Classifier, Extra Tree Classifier, Support Vector Machine, Logistic Regression, Random Forest, Ridge Classifier, Ridge Classifier CV, Bagging Classifier for classification. It also employs DNC and TNC for extraction of features. The suggested model is created using a two-layer construction strategy. The 1st layer makes a prediction about a given sequence whether it is Pi RNA or not, and the 2nd layer makes a prediction about a given PiRNA sequence whether it is having the function of instructing target mRNA dead enylation or not. Proposed model overall accuracy was 93.06 % at the first layer and 88.46 % at the second layer.