10 papers
Emergent and Frozen SCFTs from Gauge Theory
Hongliang Jiang
Four-dimensional superconformal field theories (SCFTs) are an exotic class of quantum field theories that admit no conventional Lagrangian description. In this Lett…
GlycoMAC: A Multiscale Metabolic-Glycosylation Framework for Predicting Glycosylation Across Conditions in Mammalian Cell Cultures
Yuming Zeng, Sarah W. Harcum, Jinxiang Pei +1
Antibody productivity and glycosylation quality in CHO cell cultures emerge from a dynamically evolving metabolic environment, yet existing models often work in isolation or at a s…
What drives performance in molecular MPNNs? An operator-level factorial benchmark
Panyu Jiao, Shuizhou Chen, Yiheng Shen +3
Message-passing neural networks (MPNNs) are widely used for molecular property prediction, but their deployment as monolithic architectures makes it difficult to identify how speci…
Adaptive Fast-Slow Operator Splitting for Multiscale Biochemical Stochastic Dynamics
Yuming Zeng, Wei Xie, Keqi Wang
Stochastic reaction networks governed by Chemical Langevin Equations (CLE) exhibit pronounced multiscale dynamics spanning fast molecular reactions, intermediate transport, and slo…
Intracellular Measurement-Informed Multiscale Modeling for Scalable iPSC Manufacturing
Fuqiang Cheng, Zahra Foroozan Jahromi, Keqi Wang +10
Scalable manufacturing of human induced pluripotent stem cells (iPSCs) is essential for industrial-scale production of cell therapies and regenerative medicines. However, the 3D ag…
A Modular Mechanistic In Silico Model for In Vitro Transcription Process Yield and Product Quality Prediction
Keqi Wang, Keilung Choy, Eli Reiser +10
In vitro transcription (IVT) plays a critical role in the manufacture of mRNA vaccines and therapeutics. Optimizing mRNA yield and ensuring product quality, such as capping efficie…
A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example
Keilung Choy, Wei Xie, Keqi Wang
Bioprocess mechanistic modeling is essential for advancing intelligent digital twin representation of biomanufacturing, yet challenges persist due to complex intracellular regulati…
Digital Twin Calibration with Model-Based Reinforcement Learning
Hua Zheng, Wei Xie, Ilya O. Ryzhov +1
This paper presents a novel methodological framework, called the Actor-Simulator, that incorporates the calibration of digital twins into model-based reinforcement learning for mor…
Multi-Scale Hybrid Modeling to Predict Cell Culture Process with Metabolic Phase Transitions
Keqi Wang, Sarah W. Harcum, Wei Xie
To advance understanding of cellular metabolism and reduce batch-to-batch variability in cell culture processes, this study introduces a multi-scale hybrid modeling framework desig…
Adjoint Sensitivity Analysis on Multi-Scale Bioprocess Stochastic Reaction Network
Keilung Choy, Wei Xie
Motivated by the pressing challenges in the digital twin development for biomanufacturing systems, we introduce an adjoint sensitivity analysis (SA) approach to expedite the learni…