AIMC Topic: Inhibitory Concentration 50
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Novel active Trp- and Arg-rich antimicrobial peptides with high solubility and low red blood cell toxicity designed using machine learning tools.
International journal of antimicrobial agents
Dec 5, 2024
BACKGROUND: Given the rising number of multidrug-resistant (MDR) bacteria, there is a need to design synthetic antimicrobial peptides (AMPs) that are highly active, non-hemolytic, and highly soluble. Machine learning tools allow the straightforward i...
hERGBoost: A gradient boosting model for quantitative IC prediction of hERG channel blockers.
Computers in biology and medicine
Nov 16, 2024
The human ether-a-go-go-related gene (hERG) potassium channel is pivotal in drug discovery due to its susceptibility to blockage by drug candidate molecules, which can cause severe cardiotoxic effects. Consequently, identifying and excluding potentia...
Approved drugs successfully repurposed against based on machine learning predictions.
Frontiers in cellular and infection microbiology
Sep 26, 2024
Drug repurposing is a promising approach towards the discovery of novel treatments against Neglected Tropical Diseases, such as Leishmaniases, presenting the advantage of reducing both costs and duration of the drug discovery process. In previous wor...
Anti-Biofilm: Machine Learning Assisted Prediction of IC Activity of Chemicals Against Biofilms of Microbes Causing Antimicrobial Resistance and Implications in Drug Repurposing.
Journal of molecular biology
Apr 20, 2023
Biofilms are one of the leading causes of antibiotic resistance. It acts as a physical barrier against the human immune system and drugs. The use of anti-biofilm agents helps in tackling the menace of antibiotic resistance. The identification of effi...
Integrating nonlinear analysis and machine learning for human induced pluripotent stem cell-based drug cardiotoxicity testing.
Journal of tissue engineering and regenerative medicine
May 27, 2022
Utilizing recent advances in human induced pluripotent stem cell (hiPSC) technology, nonlinear analysis and machine learning we can create novel tools to evaluate drug-induced cardiotoxicity on human cardiomyocytes. With cardiovascular disease remain...
Numerical learning of deep features from drug-exposed cell images to calculate IC50 without staining.
Scientific reports
Apr 22, 2022
To facilitate rapid determination of cellular viability caused by the inhibitory effect of drugs, numerical deep learning algorithms was used for unlabeled cell culture images captured by a light microscope as input. In this study, A549, HEK293, and ...
A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer.
Scientific reports
Aug 19, 2021
Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to identify a set of molecular markers for predicting platinum sensitivity. A signature predicting cisplat...
Performance Comparisons of AlexNet and GoogLeNet in Cell Growth Inhibition IC50 Prediction.
International journal of molecular sciences
Jul 19, 2021
Drug responses in cancer are diverse due to heterogenous genomic profiles. Drug responsiveness prediction is important in clinical response to specific cancer treatments. Recently, multi-class drug responsiveness models based on deep learning (DL) mo...
Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning.
Scientific reports
Sep 14, 2020
It is important that antibiotics prescriptions are based on antimicrobial susceptibility data to ensure effective treatment outcomes. The increasing availability of next-generation sequencing, bacterial whole genome sequencing (WGS) can facilitate a ...
Evaluation of magnesium oxide and zinc oxide nanoparticles against multi-drug-resistance Mycobacterium tuberculosis.
The Indian journal of tuberculosis
Aug 4, 2020
OBJECTIVE: The current study has evaluated the MICs and MBCs of ZnONPs, MgONPs, and MgONPs-ZnONPs against HRv Mtb and MDR-Mtb.
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