A bi-layer model for identification of piwiRNA using deep neural learning-Reference-Cited by-同舟云学术

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A bi-layer model for identification of piwiRNA using deep neural learning

Published:2023-08-22 Issue: Volume: Page:1-9
ISSN:0739-1102
Container-title:Journal of Biomolecular Structure and Dynamics
language:en
Short-container-title:Journal of Biomolecular Structure and Dynamics

Author:

Adnan Adnan¹,Hongya Wang¹,Ali Farman²,Khalid Majdi³,Alghushairy Omar⁴,Alsini Raed⁵

Affiliation:

1. School of Computer Science and Technology, Donghua University, Shanghai, China

2. Department of Software Engineering, Sarhad University of Science and Information Technology, Peshawar, Pakistan

3. Department of Computer Science, College of Computers and Information Systems, Umm Al-Qura University, Makkah, Saudi Arabia

4. Department of Information Systems and Technology, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia

5. Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

Publisher

Informa UK Limited

Subject

Molecular Biology,General Medicine,Structural Biology

Link

https://www.tandfonline.com/doi/pdf/10.1080/07391102.2023.2243523

Reference64 articles.

1. Deep-AntiFP: Prediction of antifungal peptides using distanct multi-informative features incorporating with deep neural networks

2. iAFPs-EnC-GA: Identifying antifungal peptides using sequential and evolutionary descriptors based multi-information fusion and ensemble learning approach

3. Improving secretory proteins prediction in Mycobacterium tuberculosis using the unbiased dipeptide composition with support vector machine

4. iAtbP-Hyb-EnC: Prediction of antitubercular peptides via heterogeneous feature representation and genetic algorithm based ensemble learning model

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