Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease-Reference-Cited by-同舟云学术

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Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease

Published:2024-02 Issue: Volume:245 Page:105049
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Kumar Vinay,Banerjee Arkaprava,Roy Kunal^ORCID

Funder

Indian Council of Medical Research

Defence Research and Development Organisation

Life Sciences Research Board

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference44 articles.

1. World Alzheimer Report 2022: Life after Diagnosis: Navigating Treatment, Care and Support;Gauthier,2022

2. 2022 Alzheimer's disease facts and figures;Gaugler;Alzheimer's Dementia,2022

3. Recent progress in the treatment strategies for Alzheimer's disease;Kumar;Computational Modeling of Drugs Against Alzheimer’s Disease,2023

4. Amyloid β-based therapy for Alzheimer's disease: challenges, successes and future;Zhang;Signal Transduct. Targeted Ther.,2023

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1. How safe are wild-caught salmons exposed to various industrial chemicals? First ever in silico models for salmon toxicity data gaps filling;Journal of Hazardous Materials;2024-09

2. How to correctly develop q-RASAR models for predictive cheminformatics;Expert Opinion on Drug Discovery;2024-07-05

3. Unveiling critical structural features for effective HDAC8 inhibition: a comprehensive study using quantitative read-across structure–activity relationship (q-RASAR) and pharmacophore modeling;Molecular Diversity;2024-06-13

4. A Predictive Sequence Filling Method using Protein Structures for Early Detection of Alzheimer Disease;2024-05-22

5. Breaking the Barriers: Machine-Learning-Based c-RASAR Approach for Accurate Blood–Brain Barrier Permeability Prediction;Journal of Chemical Information and Modeling;2024-05-03

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