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

作　　者：Salman Khan Mukhtaj Khan Nadeem Iqbal Mohd Amiruddin Abd Rahman Muhammad Khalis Abdul Karim 

机构地区：[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

出　　处：《Computers, Materials & Continua》2022年第8期2243-2258,共16页计算机、材料和连续体（英文）

基　　金：This research was supported by the Ministry of Higher Education(MOHE)of Malaysia through Fundamental Research Grant Scheme(FRGS/1/2020/ICT02/UPM/02/3).

摘　　要：Piwi-interacting Ribonucleic acids(piRNAs)molecule is a wellknown subclass of small non-codingRNAmolecules 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.

关 键 词：Deep neural network DNC TNC CKSNAP PseDPC cancer discovery Piwi-interacting RNAs Deep-piRNA 

分 类 号：Q343[生物学—遗传学]