Xingcheng Lin
Bio
Dr. Lin joined the Department of Physics at North Carolina State University in August 2023 and is also affiliated with the Bioinformatics Cluster of the Chancellor’s Faculty Excellence Program. He earned his Ph.D. in Biological Physics from the Center for Theoretical Biological Physics and the Physics Department at Rice University. During his graduate studies, he utilized both atomistic and coarse-grained simulations to investigate the molecular mechanisms behind the invasion of influenza viruses and intrinsically disordered proteins. He also developed simulation-based tools for predicting and refining protein structures.
Following his Ph.D., Dr. Lin conducted postdoctoral research in the Chemistry Department at the Massachusetts Institute of Technology, where he expanded his research interests to chromatin. There, he studied the organization of chromatin and its regulation by chromatin-regulating proteins.
Dr. Lin’s research group has broad interests in various areas of chemistry and biophysics, including protein-nucleic acid interactions, chromatin, epigenetics, protein folding, viral infections, and immunology. Currently, the group focuses on developing physics- and chemistry-based simulations, as well as data-driven methods, to enable predictive modeling of biomolecular interactions. Simultaneously, the group is developing deep-learning methods to integrate simulations for predicting biomolecular functions. The ultimate goal is to understand the molecular mechanisms that underlie various biological functions and their dysregulation in disease states. By leveraging the increasing availability of experimental data, the long-term research ambition is to develop predictive computational tools that quantitatively characterize biological processes, from the molecular level to the systems level. Ultimately, we aim to accelerate the design of molecules for improved therapeutic interventions that enhance human health.
Area(s) of Expertise
Our research group will employ computational modeling and simulation techniques to investigate the fundamental mechanisms of epigenetic regulation – the “dark matter” of the human genome. Leveraging an ever-increasing amount of structural and sequence data, and integrating principles of physics and chemistry, our team is dedicated to developing innovative models to explore the dynamics and functions of biomolecules critical to the organization and functions of genome and epigenome, which will pinpoint potential ways to treat diseases caused by epigenetic dysregulation. In addition, we are broadly interested in other biomolecular systems with significant applications in biomedical research and therapeutics.
Publications
- A biophysical framework for accurately identifying antigen single-amino acid escape variants and corresponding variant-specific compensatory TCR sequences , bioRxiv (Cold Spring Harbor Laboratory) (2026)
- Active regulation of the epidermal growth factor receptor by the membrane bilayer , (2026)
- Active regulation of the epidermal growth factor receptor by the membrane bilayer , eLife (2026)
- BPS2026 – Integrating sparse sequence, experimental, and AI-predicted structures for protein-nucleic acid interaction predictions , Biophysical Journal (2026)
- FlashSchNet: Fast and Accurate Coarse-Grained Neural Network Molecular Dynamics , Open MIND (2026)
- Active regulation of the epidermal growth factor receptor by the membrane bilayer , bioRxiv (Cold Spring Harbor Laboratory) (2025)
- Active regulation of the epidermal growth factor receptor by the membrane bilayer , (2025)
- Active regulation of the epidermal growth factor receptor by the membrane bilayer , eLife (2025)
- Biophysical modeling for accurate T cell specificity prediction of viral and tumor antigens , bioRxiv (Cold Spring Harbor Laboratory) (2025)
- Characterizing DNA recognition preferences of transcription factors using global couplings and high-throughput sequencing , Nucleic Acids Research (2025)