معرفی
Ya Chen is affiliated with the Department of Pharmaceutical Sciences at the Faculty of Life Sciences. Their research focuses on computational approaches in drug discovery, including virtual screening, metabolic pathway analysis, and machine learning applications. Key areas include natural product-based drug design, receptor modulation, and enzyme inhibition mechanisms. Notable contributions involve developing predictive models for drug metabolism and exploring chemical spaces for therapeutic targets like the glucocorticoid receptor. Ya Chen has presented work at international conferences and contributed to interdisciplinary projects combining cheminformatics and biological systems.
Research interests emphasize the intersection of artificial intelligence with pharmaceutical sciences, particularly in optimizing drug design workflows and understanding metabolic processes. Their work spans enzyme inhibition studies (e.g., CYP19A1, InsP3Kinase), nuclear receptor ligand discovery (RORγ, LXR), and the development of open-source tools for cheminformatics (e.g., Scikit-Mol).
Collaborative efforts involve international teams and focus on advancing methodologies for natural product screening, site-of-metabolism prediction, and chemical library design. Ya Chen’s activities highlight a commitment to bridging computational techniques with experimental pharmacology to address challenges in drug development and toxicology.
