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Machine learning and molecular docking prediction of potential inhibitors against dengue virus.
Front Chem
December 2024
African Society for Bioinformatics and Computational Biology, Cape Town, South Africa.
Introduction: Dengue Fever continues to pose a global threat due to the widespread distribution of its vector mosquitoes, and . While the WHO-approved vaccine, Dengvaxia, and antiviral treatments like Balapiravir and Celgosivir are available, challenges such as drug resistance, reduced efficacy, and high treatment costs persist. This study aims to identify novel potential inhibitors of the Dengue virus (DENV) using an integrative drug discovery approach encompassing machine learning and molecular docking techniques.
View Article and Find Full Text PDFNature's defense against emerging neurodegenerative threats: Dynamic simulation, PCA, DCCM identified potential plant-based antiviral lead targeting borna disease virus nucleoprotein.
PLoS One
January 2025
Bioinformatics Laboratory (BioLab), Noakhali, Bangladesh.
The rare zoonotic Borna disease virus (BDV) causes fatal neurological disease in various animals, with a high mortality rate exceeding 90% in central Europe. However, unlike most viruses, it establishes persistent infections within the host cell nucleus, hindering treatment. As successful BDV treatments remain elusive, the researchers turned to a computational approach, utilizing molecular docking, ADME/T, post-docking MMGBSA, MD simulation, DCCM, and PCA to identify promising phytochemical drug candidates targeting the BDV Nucleoprotein (PDB ID: 1N93).
View Article and Find Full Text PDFEstablishing minimal clinically important difference of modified dynamic gait index in people with subacute stroke.
Top Stroke Rehabil
January 2025
IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy.
Background: People with stroke (PwST) often have significant balance limitations, making it crucial to focus rehabilitation on improving mobility and reducing the risk of falls. The Modified Dynamic Gait Index (MDGI) is recommended for measuring balance in various neurological conditions, but a minimal clinically important difference (MCID) score specific to PwST is missing.
Objectives: To calculate the MCID of the MDGI in PwST during the subacute phase.
Integrating Interpretability in Machine Learning and Deep Neural Networks: A Novel Approach to Feature Importance and Outlier Detection in COVID-19 Symptomatology and Vaccine Efficacy.
Viruses
November 2024
Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our method bridges the gap between interpretable ML models and powerful deep learning (DL) architectures, providing comprehensive insights into the key drivers behind model predictions, especially in detecting outliers within medical data. We applied this method to analyze COVID-19 pandemic data from 2020, yielding intriguing insights.
View Article and Find Full Text PDFDevelopment and Evaluation of a Candidate Inactivated Vaccine Against Bluetongue Virus Serotype 4 (BTV4).
Vaccines (Basel)
November 2024
Institute of Veterinary Medicine of Serbia, Janisa Janulisa 14, 11000 Belgrade, Serbia.
Objectives: Although bluetongue is not a contagious disease, it is easily transmitted and spread by appropriate insect vectors, causing great economic damage. Climate change has led to the fact that vectors and diseases have spread to the top of Northern Europe, causing great economic losses in livestock production. An even greater problem is controlling the disease, because numerous species of domestic and wild ruminants are susceptible to bluetongue.
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