Identification of active molecules against Mycobacterium tuberculosis through machine learning

Building a tuberculosis-free world: The Lancet Commission on tuberculosis

(2019) Michael J A Reid et al.   LANCET

1 H -Benzo[ d ]imidazoles and 3,4-dihydroquinazolin-4-ones: Design, synthesis and antitubercular activity

(2018) Fernanda Souza Macchi et al.   EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY

Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery

(2018) Thomas Lane et al.   MOLECULAR PHARMACEUTICS

Design, synthesis and anti-mycobacterial activity evaluation of benzofuran-isatin hybrids

(2018) Feng Gao et al.   EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY

ChEMBL: towards direct deposition of bioassay data

(2018) David Mendez et al.   NUCLEIC ACIDS RESEARCH

ADMET Evaluation in Drug Discovery. 18. Reliable Prediction of Chemical-Induced Urinary Tract Toxicity by Boosting Machine Learning Approaches

(2017) Tailong Lei et al.   MOLECULAR PHARMACEUTICS

Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric

(2017) Sabri Boughorbel et al.   PLoS One

TensorFlow: learning functions at scale

(2016) Martín Abadi   ACM SIGPLAN NOTICES

Extreme Gradient Boosting as a Method for Quantitative Structure–Activity Relationships

(2016) Robert P. Sheridan et al.   Journal of Chemical Information and Modeling

Deep learning

(2015) Yann LeCun et al.   NATURE

Energy Metabolism and Drug Efflux in Mycobacterium tuberculosis

(2014) P. A. Black et al.   ANTIMICROBIAL AGENTS AND CHEMOTHERAPY

Looking Back to the Future: Predicting in Vivo Efficacy of Small Molecules versus Mycobacterium tuberculosis

(2014) Sean Ekins et al.   Journal of Chemical Information and Modeling

New antituberculosis drugs, regimens, and adjunct therapies: needs, advances, and future prospects

(2014) Alimuddin I Zumla et al.   LANCET INFECTIOUS DISEASES

Modern 2D QSAR for drug discovery

(2014) Richard A. Lewis et al.   Wiley Interdisciplinary Reviews-Computational Molecular Science

Drug-resistant tuberculosis: time for visionary political leadership

(2013) Ibrahim Abubakar et al.   LANCET INFECTIOUS DISEASES

Identification of Novel Imidazo[1,2-a]pyridine Inhibitors Targeting M. tuberculosis QcrB

(2013) Katherine A. Abrahams et al.   PLoS One

Construction and functionalization of fused pyridine ring leading to novel compounds as potential antitubercular agents

(2012) Balakrishna Dulla et al.   BIOORGANIC & MEDICINAL CHEMISTRY LETTERS

Synthesis and Structure–Activity Relationships of Varied Ether Linker Analogues of the Antitubercular Drug (6S)-2-Nitro-6-{[4-(trifluoromethoxy)benzyl]oxy}-6,7-dihydro-5H-imidazo[2,1-b][1,3]oxazine (PA-824)

(2011) Andrew M. Thompson et al.   JOURNAL OF MEDICINAL CHEMISTRY

When is Chemical Similarity Significant? The Statistical Distribution of Chemical Similarity Scores and Its Extreme Values

(2010) Pierre Baldi et al.   Journal of Chemical Information and Modeling

Extended-Connectivity Fingerprints

(2010) David Rogers et al.   Journal of Chemical Information and Modeling

Analysis and comparison of 2D fingerprints: Insights into database screening performance using eight fingerprint methods

(2010) Jianxin Duan et al.   JOURNAL OF MOLECULAR GRAPHICS & MODELLING

Best Practices for QSAR Model Development, Validation, and Exploitation

(2010) Alexander Tropsha   Molecular Informatics

Chemical substructures that enrich for biological activity

(2008) Justin Klekota et al.   BIOINFORMATICS

Global Bayesian Models for the Prioritization of Antitubercular Agents

(2008) Philip Prathipati et al.   Journal of Chemical Information and Modeling