pAtbP-EnC: Identifying Anti-Tubercular Peptides Using Multi-Feature Representation and Genetic Algorithm-Based Deep Ensemble Model-Reference-Cited by-同舟云学术

pAtbP-EnC: Identifying Anti-Tubercular Peptides Using Multi-Feature Representation and Genetic Algorithm-Based Deep Ensemble Model

Published:2023 Issue: Volume:11 Page:137099-137114
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Akbar Shahid¹^ORCID,Raza Ali²,Shloul Tamara Al³,Ahmad Ashfaq²,Saeed Aamir⁴^ORCID,Ghadi Yazeed Yasin⁵^ORCID,Mamyrbayev Orken⁶^ORCID,Tag-Eldin Elsayed⁷^ORCID

Affiliation:

1. Department of Computer Science, Abdul Wali Khan University Mardan, Mardan, Pakistan

2. Department of Computer Science, MY University Islamabad, Islamabad, Pakistan

3. Department of General Education, Liwa College of Technology, Abu Dhabi, United Arab Emirates

4. Department of Computer Science and IT, University of Engineering and Technology, Peshawar, Pakistan

5. Department of Computer Science, Al Ain University, Abu Dhabi, United Arab Emirates

6. Institute of Information and Computational Technologies, Almaty, Kazakhstan

7. Faculty of Engineering and Technology, Future University in Egypt, New Cairo, Egypt

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10268427.pdf?arnumber=10268427

Reference70 articles.

1. Mycobacterium tuberculosis: ecology and evolution of a human bacterium

2. Diagnosis and treatment of paediatric tuberculosis: An insight review

3. Anti-tubercular peptides: A quest of future therapeutic weapon to combat tuberculosis

4. Treatment of drug-resistant tuberculosis

5. A Machine Learning-Based Framework for the Prediction of Cervical Cancer Risk in Women

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