AIMC Topic: Mycobacterium tuberculosis
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Integrated machine learning and physics-based methods assisted de novo design of Fatty Acyl-CoA synthase inhibitors.
Expert opinion on drug discovery
Nov 25, 2024
BACKGROUND: Tuberculosis is an infectious disease that has become endemic worldwide. The causative bacteria (Mtb) is targeted via several exciting drug targets. One newly discovered target is the Fatty Acyl-CoA synthase, which plays a significant ro...
Small Molecule Inhibitors of Topoisomerase I Identified by Machine Learning and In Vitro Assays.
International journal of molecular sciences
Nov 15, 2024
Tuberculosis (TB) caused by is a leading infectious cause of death globally. The treatment of patients becomes much more difficult for the increasingly common multi-drug resistant TB. Topoisomerase I is essential for the viability of and has been v...
Leveraging large-scale Mycobacterium tuberculosis whole genome sequence data to characterise drug-resistant mutations using machine learning and statistical approaches.
Scientific reports
Nov 7, 2024
Tuberculosis disease (TB), caused by Mycobacterium tuberculosis (Mtb), is a major global public health problem, resulting in > 1 million deaths each year. Drug resistance (DR), including the multi-drug form (MDR-TB), is challenging control of the dis...
Computer vision applications for the detection or analysis of tuberculosis using digitised human lung tissue images - a systematic review.
BMC medical imaging
Nov 5, 2024
OBJECTIVE: To conduct a systematic review of the computer vision applications that detect, diagnose, or analyse tuberculosis (TB) pathology or bacilli using digitised human lung tissue images either through automatic or semi-automatic methods. We cat...
sRNAdeep: a novel tool for bacterial sRNA prediction based on DistilBERT encoding mode and deep learning algorithms.
BMC genomics
Oct 31, 2024
BACKGROUND: Bacterial small regulatory RNA (sRNA) plays a crucial role in cell metabolism and could be used as a new potential drug target in the treatment of pathogen-induced disease. However, experimental methods for identifying sRNAs still require...
Machine learning algorithms to predict treatment success for patients with pulmonary tuberculosis.
PloS one
Oct 16, 2024
Despite advancements in detection and treatment, tuberculosis (TB), an infectious illness caused by the Mycobacterium TB bacteria, continues to pose a serious threat to world health. The TB diagnosis phase includes a patient's medical history, physic...
Lite-YOLOv8: a more lightweight algorithm for Tubercle Bacilli detection.
Medical & biological engineering & computing
Sep 12, 2024
Deep learning is a transformative force in the medical field and it has made significant progress as a pivotal alternative to conventional manual testing methods. Detection of Tubercle Bacilli in sputum samples is faced with the problems of complex b...
A machine-learning based model for automated recommendation of individualized treatment of rifampicin-resistant tuberculosis.
PloS one
Sep 6, 2024
BACKGROUND: Rifampicin resistant tuberculosis remains a global health problem with almost half a million new cases annually. In high-income countries patients empirically start a standardized treatment regimen, followed by an individualized regimen g...
Identification of mycobacterial Thymidylate kinase inhibitors: a comprehensive pharmacophore, machine learning, molecular docking, and molecular dynamics simulation studies.
Molecular diversity
Aug 16, 2024
Thymidylate kinase (TMK) is a pivotal enzyme in Mycobacterium tuberculosis (Mtb), crucial for phosphorylating thymidine monophosphate (dTMP) to thymidine diphosphate (dTDP), thereby playing a critical role in DNA biosynthesis. Dysregulation or inhibi...
Prediction of Mycobacterium tuberculosis cell wall permeability using machine learning methods.
Molecular diversity
Aug 12, 2024
Tuberculosis (TB) caused by the bacteria Mycobacterium tuberculosis (M. tb), continues to pose a significant worldwide health threat. The advent of drug-resistant strains of the disease highlights the critical need for novel treatments. The unique ce...
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