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Milad Rayka

Showing results (1-10 of 8) with videos related to

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Molecular Informatics|February 1, 2023
GB-score: Minimally designed machine learning scoring function based on distance-weighted interatomic contact featuresMilad Rayka, Rohoullah Firouzi
BMC Bioinformatics|April 23, 2026
Reindeer: a protein-ligand feature generator software for machine learning algorithmsMilad Rayka, S Shahab Naghavi
Scientific Reports|December 4, 2025
Uncertainty quantification enables reliable deep learning for protein-ligand binding affinity predictionMilad Rayka, S Shahab Naghavi
Physical Chemistry Chemical Physics : PCCP|January 27, 2018
Toward a muon-specific electronic structure theory: effective electronic Hartree-Fock equations for muonic moleculesMilad Rayka, Mohammad Goli, Shant Shahbazian
Physical Chemistry Chemical Physics : PCCP|March 16, 2018
Effective electronic-only Kohn-Sham equations for the muonic moleculesMilad Rayka, Mohammad Goli, Shant Shahbazian
Molecular Informatics|February 15, 2024
An ensemble-based approach to estimate confidence of predicted protein-ligand binding affinity valuesMilad Rayka, Morteza Mirzaei, Ali Mohammad Latifi
Molecular Informatics|May 22, 2021
ET-score: Improving Protein-ligand Binding Affinity Prediction Based on Distance-weighted Interatomic Contact Features Using Extremely Randomized Trees AlgorithmMilad Rayka, Mohammad Hossein Karimi-Jafari, Rohoullah Firouzi
Scientific Reports|February 11, 2026
Interpretable machine learning rationalizes carbonic anhydrase inhibition via conformal and counterfactual predictionMasoumeh Shams Ghamsary, Milad Rayka, S Shahab Naghavi
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Molecular Informatics|February 1, 2023
GB-score: Minimally designed machine learning scoring function based on distance-weighted interatomic contact featuresMilad Rayka, Rohoullah Firouzi
BMC Bioinformatics|April 23, 2026
Reindeer: a protein-ligand feature generator software for machine learning algorithmsMilad Rayka, S Shahab Naghavi
Scientific Reports|December 4, 2025
Uncertainty quantification enables reliable deep learning for protein-ligand binding affinity predictionMilad Rayka, S Shahab Naghavi
Physical Chemistry Chemical Physics : PCCP|January 27, 2018
Toward a muon-specific electronic structure theory: effective electronic Hartree-Fock equations for muonic moleculesMilad Rayka, Mohammad Goli, Shant Shahbazian
Physical Chemistry Chemical Physics : PCCP|March 16, 2018
Effective electronic-only Kohn-Sham equations for the muonic moleculesMilad Rayka, Mohammad Goli, Shant Shahbazian
Molecular Informatics|February 15, 2024
An ensemble-based approach to estimate confidence of predicted protein-ligand binding affinity valuesMilad Rayka, Morteza Mirzaei, Ali Mohammad Latifi
Molecular Informatics|May 22, 2021
ET-score: Improving Protein-ligand Binding Affinity Prediction Based on Distance-weighted Interatomic Contact Features Using Extremely Randomized Trees AlgorithmMilad Rayka, Mohammad Hossein Karimi-Jafari, Rohoullah Firouzi
Scientific Reports|February 11, 2026
Interpretable machine learning rationalizes carbonic anhydrase inhibition via conformal and counterfactual predictionMasoumeh Shams Ghamsary, Milad Rayka, S Shahab Naghavi
Pageof 1