Pin-Kuang Lai

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Toward Metagenome-Scale Metabolic Flux and Free Energy Analysis via Deep Learning
Park, J. O. J. O. (PI) & Lai, P.-K. (CoPI)
1/09/23 → 31/08/26
Project: Research project

24 Article
3 Conference contribution

Accelerating high-concentration monoclonal antibody development with large-scale viscosity data and ensemble deep learning
Kalejaye, L. A., Chu, J. M., Wu, I. E., Amofah, B., Lee, A., Hutchinson, M., Chakiath, C., Dippel, A., Kaplan, G., Damschroder, M., Stanev, V., Pouryahya, M., Boroumand, M., Caldwell, J., Hinton, A., Kreitz, M., Shah, M., Gallegos, A., Mody, N. & Lai, P. K., 2025, In: mAbs. 17, 1, 2483944.
Research output: Contribution to journal › Article › peer-review

Open Access
5 Scopus citations
Kinetic analysis of low-barrier nucleation via first-passage time distributions: A CO₂ hydrate case study
Huang, L. Y., Lai, P. K. & Lin, S. T., 15 Jan 2025, In: Journal of Molecular Liquids. 418, 126702.
Research output: Contribution to journal › Article › peer-review
4 Scopus citations
Machine Learning Models for Predicting Monoclonal Antibody Biophysical Properties from Molecular Dynamics Simulations and Deep Learning-Based Surface Descriptors
Wu, I. E., Kalejaye, L. & Lai, P. K., 6 Jan 2025, In: Molecular Pharmaceutics. 22, 1, p. 142-153 12 p.
Research output: Contribution to journal › Article › peer-review
8 Scopus citations
Physics-guided estimation of mean first-passage times from censored nucleation trajectories
Huang, L. Y., Lai, P. K. & Lin, S. T., 28 Jul 2025, In: Journal of Chemical Physics. 163, 4, 044101.
Research output: Contribution to journal › Article › peer-review
Predicting Subcutaneous Antibody Bioavailability Using Ensemble Protein Language Models
Cabreza, M., Hojegian, W., Wu, I. E. & Lai, P. K., 1 Sep 2025, In: Molecular Pharmaceutics. 22, 9, p. 5504-5511 8 p.
Research output: Contribution to journal › Article › peer-review

Pin-Kuang Lai

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Collaborations and top research areas from the last five years

Dive into details

Toward Metagenome-Scale Metabolic Flux and Free Energy Analysis via Deep Learning

Accelerating high-concentration monoclonal antibody development with large-scale viscosity data and ensemble deep learning

Kinetic analysis of low-barrier nucleation via first-passage time distributions: A CO₂ hydrate case study

Machine Learning Models for Predicting Monoclonal Antibody Biophysical Properties from Molecular Dynamics Simulations and Deep Learning-Based Surface Descriptors

Physics-guided estimation of mean first-passage times from censored nucleation trajectories

Predicting Subcutaneous Antibody Bioavailability Using Ensemble Protein Language Models

Pin-Kuang Lai

Fingerprint

Collaborations and top research areas from the last five years

Projects

Toward Metagenome-Scale Metabolic Flux and Free Energy Analysis via Deep Learning

Research output

Accelerating high-concentration monoclonal antibody development with large-scale viscosity data and ensemble deep learning

Kinetic analysis of low-barrier nucleation via first-passage time distributions: A CO2 hydrate case study

Machine Learning Models for Predicting Monoclonal Antibody Biophysical Properties from Molecular Dynamics Simulations and Deep Learning-Based Surface Descriptors

Physics-guided estimation of mean first-passage times from censored nucleation trajectories

Predicting Subcutaneous Antibody Bioavailability Using Ensemble Protein Language Models

Kinetic analysis of low-barrier nucleation via first-passage time distributions: A CO₂ hydrate case study