Open Access iconOpen Access

ARTICLE

crossmark

Deep-piRNA: Bi-Layered Prediction Model for PIWI-Interacting RNA Using Discriminative Features

Salman Khan1, Mukhtaj Khan1,2, Nadeem Iqbal1, Mohd Amiruddin Abd Rahman3,*, Muhammad Khalis Abdul Karim3

1 Department of Computer Science, Abdul Wali Khan University Mardan, Khyber Pakhtunkhwa, 23200, Pakistan
2 Department of Information Technology, University of Haripur, Khyber Pakhtunkhwa, 22620, Pakistan
3 Faculty of Science, Universiti Putra Malaysia, UPM Serdang, 43400, Malaysia

* Corresponding Author: Mohd Amiruddin Abd Rahman. Email: email

Computers, Materials & Continua 2022, 72(2), 2243-2258. https://doi.org/10.32604/cmc.2022.022901

Abstract

Piwi-interacting Ribonucleic acids (piRNAs) molecule is a well-known subclass of small non-coding RNA molecules that are mainly responsible for maintaining genome integrity, regulating gene expression, and germline stem cell maintenance by suppressing transposon elements. The piRNAs molecule can be used for the diagnosis of multiple tumor types and drug development. Due to the vital roles of the piRNA in computational biology, the identification of piRNAs has become an important area of research in computational biology. This paper proposes a two-layer predictor to improve the prediction of piRNAs and their function using deep learning methods. The proposed model applies various feature extraction methods to consider both structure information and physicochemical properties of the biological sequences during the feature extraction process. The outcome of the proposed model is extensively evaluated using the k-fold cross-validation method. The evaluation result shows that the proposed predictor performed better than the existing models with accuracy improvement of 7.59% and 2.81% at layer I and layer II respectively. It is anticipated that the proposed model could be a beneficial tool for cancer diagnosis and precision medicine.

Keywords


Cite This Article

APA Style
Khan, S., Khan, M., Iqbal, N., Rahman, M.A.A., Karim, M.K.A. (2022). Deep-pirna: bi-layered prediction model for piwi-interacting RNA using discriminative features. Computers, Materials & Continua, 72(2), 2243-2258. https://doi.org/10.32604/cmc.2022.022901
Vancouver Style
Khan S, Khan M, Iqbal N, Rahman MAA, Karim MKA. Deep-pirna: bi-layered prediction model for piwi-interacting RNA using discriminative features. Comput Mater Contin. 2022;72(2):2243-2258 https://doi.org/10.32604/cmc.2022.022901
IEEE Style
S. Khan, M. Khan, N. Iqbal, M.A.A. Rahman, and M.K.A. Karim, “Deep-piRNA: Bi-Layered Prediction Model for PIWI-Interacting RNA Using Discriminative Features,” Comput. Mater. Contin., vol. 72, no. 2, pp. 2243-2258, 2022. https://doi.org/10.32604/cmc.2022.022901

Citations




cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 2034

    View

  • 841

    Download

  • 0

    Like

Share Link