Machine learning model predicts protein binding on gold nanoclusters

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...
EurekAlert!

Machine Learning Model predict protein binding on gold nanoclusters - Opens doors for next-generation biomedical nanomaterials

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...

Machine learning offers growers a new tool for predicting crop water use

A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant ...
The Regulatory Review

Predicting Turbidity, Protecting Tap Water

Scholars analyze how the use of machine learning could reshape EPA drinking water standards.
Chromatography Online

A Novel Machine Learning Method for Predicting Retention Time of Small Molecule Pharmaceutical Compounds Across Reversed-phase HPLC Columns

Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
Medical Dialogues

Machine Learning Reliably Predicts Early Dysphagia After Stroke, suggests study

According to a new study, machine learning can reliably identify patients at high risk of early dysphagia following acute ...
Nanowerk

Machine Learning model predicts protein binding on gold nanoclusters for biomedicine

A generalizable ML framework predicts protein interactions with ligand-stabilized gold nanoclusters, supporting faster design ...

Machine learning models could help diagnose ALS earlier through blood biomarkers

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic ...

Machine learning offers new way to predict plant water use, Israeli study finds

A new Israeli study suggests that machine-learning models may soon give growers a far more precise way to predict how much water their crops use each day, while also laying the groundwork for earlier ...

New model makes machine learning potentials more accurate and more accessible

A study in Nature Communications by Michele Ceriotti’s group at EPFL has introduced a new dataset and model that greatly improve the efficiency of machine-learning interatomic potentials (MLIPs) and ...