Tieu-Long Phan

Nhà nghiên cứu Hồ sơ 6/10

49 công bố · 68 trích dẫn · h-index 5

Thông tin

🏛️Nơi công tác: Đại học Y Dược TP.HCM
🔬Lĩnh vực: Dược học
🆔ORCID: 0000-0002-3532-2064
✍️Hồ sơ chưa đầy đủ — bổ sung thông tin

Chỉ số h-index 5 xếp học giả này vào lĩnh vực Dược học, thuộc nhóm 25% dẫn đầu trong 1.174 hồ sơ cùng lĩnh vực của danh bạ này.

Công bố tiêu biểu

Novel machine learning approach toward classification model of HIV-1 integrase inhibitors10 trích dẫn
RSC Advances · 2024 · DOI

KGG : Knowledge-Guided Graph Self-Supervised Learning to Enhance Molecular Property Predictions9 trích dẫn
Journal of Chemical Information and Modeling · 2025 · DOI

SynTemp : Efficient Extraction of Graph-Based Reaction Rules from Large-Scale Reaction Databases8 trích dẫn
Journal of Chemical Information and Modeling · 2025 · DOI

Partial Imaginary Transition State (ITS) Graphs: A Formal Framework for Research and Analysis of Atom-to-Atom Maps of Unbalanced Chemical Reactions and Their Completions6 trích dẫn
Symmetry · 2024 · DOI

Reaction rebalancing: a novel approach to curating reaction databases5 trích dẫn
Journal of Cheminformatics · 2024 · DOI

Integration of the Butina algorithm and ensemble learning strategies for the advancement of a pharmacophore ligand-based model: an in silico investigation of apelin agonists3 trích dẫn
Frontiers in Chemistry · 2024 · DOI

Innovative Integration of Butina Clustering with Ensemble Learning Techniques for the Refined Pharmacophore Modeling of Apelin Receptor Agonists: A High-Impact Computational Approach3 trích dẫn
ChemRxiv · 2024 · DOI

Discovery of Vascular Endothelial Growth Factor Receptor 2 Inhibitors Employing Junction Tree Variational Autoencoder with Bayesian Optimization and Gradient Ascent3 trích dẫn
ACS Omega · 2024 · DOI

A Graph Neural Network Model Enables Accurate Prediction of Anaplastic Lymphoma Kinase Inhibitors Compared to Other Machine Learning Models2 trích dẫn
· 2023 · DOI

Synergy of advanced machine learning and deep neural networks with consensus molecular docking for virtual screening of anaplastic lymphoma kinase inhibitors2 trích dẫn
Journal of Computer-Aided Molecular Design · 2025 · DOI

Về lĩnh vực Dược học

1.174học giả

16.750công bố

196.254trích dẫn

4.2h-index trung bình

Hướng nghiên cứu phổ biến trong lĩnh vực:

Natural product bioactivities and synthesisEssential Oils and Antimicrobial ActivityPhytochemistry and Biological ActivitiesPhytochemicals and Antioxidant ActivitiesComputational Drug Discovery MethodsMicrobial Natural Products and Biosynthesis

Nơi có nhiều học giả lĩnh vực này nhất: