A comparative study of antibiotic resistance patterns in Mycobacterium tuberculosis
The study uses the Bacterial and Viral Bioinformatics Resource Center to analyze 27,000 Mycobacterium tuberculosis genomic strains, providing a comprehensive overview of antibiotic resistance prevalence and patterns. It uses MTB++, an AI-based tool, to predict resistance profiles and identify key genes associated with resistance. The study highlights the need for targeted diagnostics and personalized treatment plans, highlighting computational limitations and recommending future experimental validation.
OUR UNDERWRITERS
Unrestricted financial support by:
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Antimicrobial Resistance Fighter Coalition |
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Bangalore Bioinnovation Centre |
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INTERNATIONAL FEDERATION PHARMACEUTICAL MANUFACTURERS & ASSOCIATIONS |
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BD |
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