Food research international (Ottawa, Ont.)
40022379
Latitude differences can significantly affect the quality of tea, while in-depth research in this field is lacking. This study investigates green teas from different latitudes in China using thermogravimetric analysis coupled with infrared spectrosco...
The prediction of enzyme kinetic parameters is crucial for screening enzymes with high catalytic efficiency and desired characteristics to catalyze natural or non-natural reactions. Data-driven machine learning models have been explored to reduce exp...
Accurate prediction of enzyme kinetic parameters is crucial for enzyme exploration and modification. Existing models face the problem of either low accuracy or poor generalization ability due to overfitting. In this work, we first developed unbiased ...
International journal of biological macromolecules
40101811
This study focuses on optimizing the fermentation process for the production of low molecular weight welan gum (LMW-WG) using Sphingomonas sp. ATCC 31555 with glycerol as the sole carbon source. A series of single-factor experiments were conducted to...
Dynamic variables contribute to understand the mechanics of pedalling and can assist with injury prevention. Measuring pedal forces and joint moments and powers has a high cost, which can be mitigated by using trained artificial neural networks (ANN)...
Physics-informed machine learning bridges the gap between the high fidelity of mechanistic models and the adaptive insights of artificial intelligence. In chemical reaction network modeling, this synergy proves valuable, addressing the high computati...
In the manufacturing of therapeutic monoclonal antibodies (mAbs), mechanistic models can aid the evaluation and selection of suitable chromatography operating conditions during process development. However, model calibration remains a common bottlene...
Traditional methods for synthesizing nanozymes are often time-consuming and complex, hindering efficiency. Artificial intelligence (AI) has the potential to simplify these processes, but there are very few dedicated nanozyme databases available, limi...
Chemical reaction neural networks (CRNN) and density functional theory (DFT) are gaining attention in biomass pyrolysis mechanism research. Reaction pathways are often speculated based on a single method, influenced by expert knowledge. To address th...
Machine learning (ML) tools have revolutionized protein structure prediction, engineering, and design, but the best ML tool is only as good as the training data it learns from. To obtain high-quality structural or functional data, protein purificatio...