Prediction of Antitubercular Peptides From Sequence Information Using Ensemble Classifier and Hybrid Features

Prediction of Antitubercular Peptides From Sequence Information Using Ensemble Classifier and Hybrid Features

Tuberculosis is one of the leading cause of death worldwide, particularly due to evolution of drug resistant strains. Antitubercular peptides may provide an alternate approach to combat antibiotic tolerance. Sequence analysis reveals that certain residues (e.g., Lysine, Arginine, Leucine, Tryptophan...

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Bibliographic Details
Main Authors: Salman Sadullah Usmani, Sherry Bhalla, Gajendra P. S. Raghava
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-08-01
Series:Frontiers in Pharmacology
Subjects:
tuberculosis
antitubercular peptides
machine learning
antimycobacterial therapy
Mycobacterium
ensemble classifier
Online Access:https://www.frontiersin.org/article/10.3389/fphar.2018.00954/full

Internet

https://www.frontiersin.org/article/10.3389/fphar.2018.00954/full

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