Machine Learning Models for Mycobacterium tuberculosis In Vitro Activity: Prediction and Target Visualization

Author:

Lane Thomas R.1,Urbina Fabio1,Rank Laura1,Gerlach Jacob1,Riabova Olga2,Lepioshkin Alexander2,Kazakova Elena2,Vocat Anthony3,Tkachenko Valery4,Cole Stewart5,Makarov Vadim2,Ekins Sean1ORCID

Affiliation:

1. Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States

2. Research Center of Biotechnology RAS, Moscow 119071, Russia

3. Global Health Institute, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland

4. Science Data Experts, 14909 Forest Landing Cir, Rockville, Maryland 20850, United States

5. Institut Pasteur, Paris 75015, France

Funder

National Institute of Environmental Health Sciences

National Center for Complementary and Alternative Medicine

European Commission

Russian Science Foundation

National Institute of General Medical Sciences

Publisher

American Chemical Society (ACS)

Subject

Drug Discovery,Pharmaceutical Science,Molecular Medicine

Reference119 articles.

1. World Health Organisation. Global Tuberculosis Report 2020. https://www.who.int/publications/i/item/9789240013131 (accessed Dec 20, 2021).

2. Multidrug-Resistant Tuberculosis and Extensively Drug-Resistant Tuberculosis

3. Adverse Effects and Choice between the Injectable Agents Amikacin and Capreomycin in Multidrug-Resistant Tuberculosis

4. TB Alliance. Inadequate Treatment. https://www.tballiance.org/why-new-tb-drugs/inadequate-treatment (accessed Dec 20, 2021).

5. Twenty Years of Global Surveillance of Antituberculosis-Drug Resistance

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