Computational analysis and prediction of PE_PGRS proteins using machine learning

Computational analysis and prediction of PE_PGRS proteins using machine learning

Mycobacterium tuberculosis genome comprises approximately 10% of two families of poorly characterised genes due to their high GC content and highly repetitive nature. The largest sub-group, the proline-glutamic acid polymorphic guanine-cytosine-rich sequence (PE_PGRS) family, is thought to be involv...

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Bibliographic Details
Main Authors: Fuyi Li, Xudong Guo, Dongxu Xiang, Miranda E. Pitt, Arnold Bainomugisa, Lachlan J.M. Coin
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:Computational and Structural Biotechnology Journal
Subjects:
PE_PGRS
Bioinformatics
Sequence analysis
Machine learning
Mycobacterial
Online Access:http://www.sciencedirect.com/science/article/pii/S2001037022000265

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http://www.sciencedirect.com/science/article/pii/S2001037022000265

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