T7 RNA Polymerase (RNAP) is a widely used enzyme with recent applications in the production of RNA vaccines. For over 50 years denaturing sequencing gels have been used as key analysis tools for probing the nucleotide addition mechanisms of T7 RNAP a...
The use of time lapse systems (TLS) in In Vitro Fertilization (IVF) labs to record developing embryos has paved the way for deep-learning based computer vision algorithms to assist embryologists in their morphokinetic evaluation. Today, most of the l...
We investigate the application of deep learning in comparing gait cycle time series from two groups of healthy children, each assessed in different gait laboratories. Both laboratories used similar gait analysis protocols with minimal differences in ...
The patch clamp technique is a fundamental tool for investigating ion channel dynamics and electrophysiological properties. This study proposes the first artificial intelligence framework for characterizing multiple ion channel kinetics of whole-cell...
Machine learning is an effective tool for predicting reaction rate constants for many organic compounds with the hydroxyl radical (HO). Previously reported models have achieved relatively good performance, but due to scarce data (<1400 records), the ...
Nitrous acid (HONO) serves as the primary source of OH radicals in the atmosphere, exerting significant impacts on atmospheric secondary pollution. The heterogeneous reactions of NO on surfaces and photolysis of particulate nitrate or adsorbed nitric...
Single-molecule fluorescence resonance energy transfer (smFRET) has emerged as a pivotal technique for probing biomolecular dynamics over time at nanometer scales. Quantitative analyses of smFRET time traces remain challenging due to confounding fact...
Cobalt-doped zinc oxide nanoparticles were fabricated and examined in this study as a potential photocatalyst for the antibiotic ciprofloxacin (CIPF) degradation when exposed to visible LED light. The Co-precipitation technique created Cobalt-doped z...
Generative artificial intelligence (AI) models trained on natural protein sequences have been used to design functional enzymes. However, their ability to predict individual reaction steps in enzyme catalysis remains unclear, limiting the potential u...
The enzyme turnover number (k) is crucial for understanding enzyme kinetics and optimizing biotechnological processes. However, experimentally measured k values are limited due to the high cost and labor intensity of wet-lab measurements, necessitati...