AIMC Topic: Mycobacterium tuberculosis
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A Deep Learning Approach to Antibiotic Discovery.
Cell
Feb 20, 2020
Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we trained a deep neural network capable of predicting molecules with antibacterial activity. We performed pr...
Recent Advancement in Predicting Subcellular Localization of Mycobacterial Protein with Machine Learning Methods.
Medicinal chemistry (Shariqah (United Arab Emirates))
Jan 1, 2020
Mycobacterium tuberculosis (MTB) can cause the terrible tuberculosis (TB), which is reported as one of the most dreadful epidemics. Although many biochemical molecular drugs have been developed to cope with this disease, the drug resistance-especiall...
Hybrid Design of Isonicotinic Acid Hydrazide Derivatives: Machine Learning Studies, Synthesis and Biological Evaluation of their Antituberculosis Activity.
Current drug discovery technologies
Jan 1, 2020
BACKGROUND: Tuberculosis (TB) is an infection disease caused by Mycobacterium tuberculosis (Mtb) bacteria. One of the main causes of mortality from TB is the problem of Mtb resistance to known drugs.
Precision immunoprofiling to reveal diagnostic signatures for latent tuberculosis infection and reactivation risk stratification.
Integrative biology : quantitative biosciences from nano to macro
Jan 1, 2019
Latent tuberculosis infection (LTBI) is estimated in nearly one quarter of the world's population, and of those immunocompetent and infected ~10% will proceed to active tuberculosis (TB). Current diagnostics cannot definitively identify LTBI and prov...
Antigens
Photons
Immunoassay
Workflow
Mycobacterium tuberculosis
Diagnostic Tests, Routine
Silicon
Latent Tuberculosis
Tuberculin Test
Immune System
Risk Assessment
Leukocytes, Mononuclear
Computational Biology
Mass Screening
Humans
Machine Learning
Algorithms
Cytokines
Prospective Studies
Adult
Biomarkers
Male
Female
Middle Aged
Aged
Computational Approaches as Rational Decision Support Systems for Discovering Next-Generation Antitubercular Agents: Mini-Review.
Current computer-aided drug design
Jan 1, 2019
Tuberculosis, malaria, dengue, chikungunya, leishmaniasis etc. are a large group of neglected tropical diseases that prevail in tropical and subtropical countries, affecting one billion people every year. Minimal funding and grants for research on th...
Levofloxacin Pharmacokinetics/Pharmacodynamics, Dosing, Susceptibility Breakpoints, and Artificial Intelligence in the Treatment of Multidrug-resistant Tuberculosis.
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Nov 28, 2018
BACKGROUND: Levofloxacin is used for the treatment of multidrug-resistant tuberculosis; however the optimal dose is unknown.
Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data.
Bioinformatics (Oxford, England)
May 15, 2018
MOTIVATION: Correct and rapid determination of Mycobacterium tuberculosis (MTB) resistance against available tuberculosis (TB) drugs is essential for the control and management of TB. Conventional molecular diagnostic test assumes that the presence o...
Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning.
GigaScience
May 1, 2018
Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex elec...
Cheminformatics Based Machine Learning Approaches for Assessing Glycolytic Pathway Antagonists of Mycobacterium tuberculosis.
Combinatorial chemistry & high throughput screening
Jan 1, 2016
BACKGROUND: Tuberculosis is the second leading cause of death from an infectious disease worldwide after HIV, thus reasoning the expeditions in antituberculosis research. The rising number of cases of infection by resistant forms of M. tuberculosis h...
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