The-Chuong Trinh

The-Chuong Trinh

PhD student in Bioinformatics at the Gen&Chem lab (BGE). Pharmacist and Master's degree holder in BioHealth Engineering with expertise in applying ML/DL methodologies to Computer-Aided Drug Discovery.

Posts by Collection

portfolio

MolUtil

MolUtil is an automated pipeline for molecular standardization, featurization into molecular descriptors and fingerprints, medicinal chemistry filtration, and chemical space visualization

MLQSAR

Mlqsar is a comprehensive automated QSAR workflow facilitating benchmark analysis and data category selection via rigorous statistical evaluation

MolAD

MolAD helps identify the applicability domain of QSAR models using PCA or MDS dimension reduction with the convex hull.

Statistical_test

Statistical test improves decision-making in comparing machine learning models’ performance by implementing statistical tests, including Bayesian estimation and the Wilcoxon signed-rank test

project

SynOmicsBench

SynOmicsBench is the first benchmarking study tailored to high-dimensional clinical transcriptomic cancer data, comparing synthetic data generation methods across three clinical cancer trials.

MIL 3D-GNN for Cdr1 Inhibitor Screening

This Master’s project explores the application of Multi-Instance Learning (MIL) 3D Graph Neural Networks for discovering novel inhibitors of the Candida albicans Cdr1 efflux pump.

publications

Application of machine learning in virtual screening of HIV integrase inhibitors

Published in Vietnamese Pharmacy Journal, 2022

Applications of machine learning in drug design is an emerging and fast-growing field of research. In silico models allow the speeding up of drug discovery and developments…

Recommended citation: Tieu Long Phan, Xuan Truc Tran Dinh, The Chuong Trinh, Hoang Son Le Lai, Ngoc Tuyen Truong (2022). Application of machine learning in virtual screening of HIV integrase inhibitors - Vietnamese Pharmacy Journal, 506, 21-25.

A graph neural network model enables accurate prediction of Anaplastic lymphoma kinase inhibitors compared to other machine learning models

Published in 15th International Conference on Knowledge and Systems Engineering (KSE), 2023

Anaplastic lymphoma kinase (ALK), a tyrosine kinase receptor, is defined as an important target in the development of anticancer drugs for non-small cell lung cancer…

Recommended citation: T. -C. Trinh et al., "A Graph Neural Network Model Enables Accurate Prediction of Anaplastic Lymphoma Kinase Inhibitors Compared to Other Machine Learning Models," 2023 15th International Conference on Knowledge and Systems Engineering (KSE), Hanoi, Vietnam, 2023, pp. 1-6, doi: 10.1109/KSE59128.2023.10299477. https://ieeexplore.ieee.org/abstract/document/10299477

Synergy of advanced machine learning and deep neural networks with consensus molecular docking for virtual screening of anaplastic lymphoma kinase inhibitors

Published in Journal of Computer-Aided Molecular Design, 2025

This study addresses the urgent need for an AI model to predict Anaplastic Lymphoma Kinase (ALK) inhibitors for Non-Small Cell Lung Cancer treatment, targeting the ALK-positive mutation…

Recommended citation: Trinh, T.C., et al. Synergy of advanced machine learning and deep neural networks with consensus molecular docking for virtual screening of anaplastic lymphoma kinase inhibitors. J Comput Aided Mol Des 39, 7 (2025). https://doi.org/10.1007/s10822-025-00657-6 https://link.springer.com/article/10.1007/s10822-025-00657-6

Ligand-Based Drug Discovery Leveraging State-of-the-Art Machine Learning Methodologies Exemplified by Cdr1 Inhibitor Prediction

Published in Journal of Chemical Information and Modeling (JCIM), 2025

In this study, we employed state-of-the-art machine learning methods, including Multi-Instance Learning (MIL) 3D Graph Neural Networks, to predict inhibitors for the Candida albicans Cdr1 efflux pump…

Recommended citation: The-Chuong Trinh, Pierre Falson, Viet-Khoa Tran-Nguyen, and Ahcène Boumendjel. Ligand-Based Drug Discovery Leveraging State-of-the-Art Machine Learning Methodologies Exemplified by Cdr1 Inhibitor Prediction. Journal of Chemical Information and Modeling 2025. DOI: 10.1021/acs.jcim.5c00374 https://pubs.acs.org/doi/abs/10.1021/acs.jcim.5c00374

talks

teaching

Cheminformatics

Internal training, University of Medicine and Pharmacy at Ho Chi Minh city, Department of Organic Chemistry, 2022

This is a set of eight (8) tutorials on basic information of cheminformatics using the Google Colab free cloud-computing environment in Summer 2022.

Molecular Docking

Internal training, University of Medicine and Pharmacy at Ho Chi Minh city, Department of Organic Chemistry, 2022

This is a set of two (2+) tutorials on basic information of molecular docking incoporating python framework, using the Google Colab free cloud-computing environment in Fall 2022.

Deep Learning

Internal training, University of Medicine and Pharmacy at Ho Chi Minh city, Department of Organic Chemistry, 2023

This is a set of four (4+) tutorials on basic information of deep learning in drug discovery incoporating tensorflow and pytorch framework, using the Google Colab free cloud-computing environment in Spring 2023.

Molecular Docking Colab

Internal training, University of Medicine and Pharmacy at Ho Chi Minh city, Department of Organic Chemistry, 2023

This is a set of two (4) tutorials on basic information of molecular docking incoporating python framework, using the Google Colab free cloud-computing environment in Summer 2023. You can watch this tutorial to learn how to use Google Colab. Please download the presentation here. Or you can read the Vietnamse document.