Phasit Charoenkwan

Chiang Mai, 50200, Thailand

Last Updated: 09/26/2026

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Found 59 publications

Interpretable QSAR modelling for PPAR-γ agonist prediction by integrating a stacking strategy, docking, and MD simulations.

Interpretable QSAR modelling for PPAR-γ agonist prediction by integrating a stacking strategy, docking, and MD simulations.

Journal: Molecular diversity

Published: April 01, 2026

iMRSA-Fuse: A Fast and Accurate Computational Approach for Predicting Anti-MRSA Peptides by Fusing Multi-View Information.

iMRSA-Fuse: A Fast and Accurate Computational Approach for Predicting Anti-MRSA Peptides by Fusing Multi-View Information.

Journal: IEEE transactions on computational biology and bioinformatics

Published: August 14, 2025

Machine learning-based cfDNA fragmentation profiling using automated capillary electrophoresis for early detection of hepatocellular carcinoma.

Machine learning-based cfDNA fragmentation profiling using automated capillary electrophoresis for early detection of hepatocellular carcinoma.

Journal: Communications medicine

Published: June 05, 2025

PSR-MAPMS: A new approach for the interpretable prediction of myelin autoantigenic peptides in multiple sclerosis using multi-source propensity scores.

PSR-MAPMS: A new approach for the interpretable prediction of myelin autoantigenic peptides in multiple sclerosis using multi-source propensity scores.

Journal: Protein science : a publication of the Protein Society

Published: September 09, 2024

MetaCGRP is a high-precision meta-model for large-scale identification of CGRP inhibitors using multi-view information.

MetaCGRP is a high-precision meta-model for large-scale identification of CGRP inhibitors using multi-view information.

Journal: Scientific reports

Published: July 24, 2024

Stack-AVP: A Stacked Ensemble Predictor Based on Multi-view Information for Fast and Accurate Discovery of Antiviral Peptides.

Stack-AVP: A Stacked Ensemble Predictor Based on Multi-view Information for Fast and Accurate Discovery of Antiviral Peptides.

Journal: Journal of molecular biology

Published: July 11, 2024

Deepstack-ACE: A deep stacking-based ensemble learning framework for the accelerated discovery of ACE inhibitory peptides.

Deepstack-ACE: A deep stacking-based ensemble learning framework for the accelerated discovery of ACE inhibitory peptides.

Journal: Methods (San Diego, Calif.)

Published: June 21, 2024

Accelerating the identification of the allergenic potential of plant proteins using a stacked ensemble-learning framework.

Accelerating the identification of the allergenic potential of plant proteins using a stacked ensemble-learning framework.

Journal: Journal of biomolecular structure & dynamics

Published: February 22, 2024

Machine-learning-assisted high-throughput identification of potent and stable neutralizing antibodies against all four dengue virus serotypes.

Machine-learning-assisted high-throughput identification of potent and stable neutralizing antibodies against all four dengue virus serotypes.

Journal: Scientific reports

Published: December 15, 2023

TROLLOPE: A novel sequence-based stacked approach for the accelerated discovery of linear T-cell epitopes of hepatitis C virus.

TROLLOPE: A novel sequence-based stacked approach for the accelerated discovery of linear T-cell epitopes of hepatitis C virus.

Journal: PloS one

Published: June 07, 2023

StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens.

StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens.

Journal: BMC bioinformatics

Published: April 11, 2023

TIPred: a novel stacked ensemble approach for the accelerated discovery of tyrosinase inhibitory peptides.

TIPred: a novel stacked ensemble approach for the accelerated discovery of tyrosinase inhibitory peptides.

Journal: BMC bioinformatics

Published: March 30, 2023

Showing 1-12 of 59

Last Updated: 09/26/2026