A Graph Neural Network Model Enables Accurate Prediction of Anaplastic Lymphoma Kinase Inhibitors Compared to Other Machine Learning Models. - The-Chuong Trinh; Tieu-Long Phan; Van-Thinh To; Gia-Bao Truong; Thanh-An Pham; Hoang-Son Lai Le; Phuoc-Chung van Nguyen; Tuyen Ngoc Truong (KSE, 2023)

Partial Imaginary Transition State (ITS) Graphs: A Formal Framework for Research and Analysis of Atom-to-Atom Maps of Unbalanced Chemical Reactions and Their Completions. - Marcos E. González Laffitte; Klaus Weinbauer; Tieu-Long Phan; Nora Beier; Nico Domschke; Christoph Flamm; Thomas Gatter; Daniel Merkle; Peter F. Stadler (Symmetry, 2024)

Reaction rebalancing: a novel approach to curating reaction databases. - Tieu-Long Phan; Klaus Weinbauer; Thomas Gärtner 001; Daniel Merkle; Jakob L. Andersen; Rolf Fagerberg; Peter F. Stadler (J. Cheminformatics, 2024)

Extension of Partial Atom-To-Atom Maps: Uniqueness and Algorithms. - Marcos E. González Laffitte; Tieu-Long Phan; Peter F. Stadler (WABI, 2025)

SynTemp: Efficient Extraction of Graph-Based Reaction Rules from Large-Scale Reaction Databases. - Tieu-Long Phan; Klaus Weinbauer; Marcos E. González Laffitte; Yingjie Pan; Daniel Merkle; Jakob L. Andersen; Rolf Fagerberg; Christoph Flamm; Peter F. Stadler (J. Chem. Inf. Model., 2025)