Development of Machine Learning Regression Model for COVID-19 Drug Target Prediction
Author:
Affiliation:
1. Georgia Institute of Technology,Wallace H. Coulter Department of Biomedical Engineering,Atlanta,Georgia,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9994793/9994847/09995319.pdf?arnumber=9995319
Reference28 articles.
1. CDC Museum COVID-19 Timeline,2022
2. Automating drug discovery
3. Recognizing molecules with drug-like properties
4. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings
5. Applications of machine learning in drug discovery and development
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1. Development of Interpretable Machine Learning Models for COVID-19 Drug Target Docking Scores Prediction;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05
2. Effective Surrogate Models for Docking Scores Prediction of Candidate Drug Molecules on SARS-CoV-2 Protein Targets;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05
3. Model Confidence Calibration for Reliable COVID-19 Early Screening via Audio Signal Analysis;Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics;2023-09-03
4. Accuracy and Performance of Machine Learning Methodologies: Novel Assessments of Country Pandemic Vulnerability Based on Non-Pandemic Predictors;IEEE Access;2023
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