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

Crystal structure prediction is, after years of hard work by many, many groups, finally reaching the point where it’s going to have large impacts in organic materials.’ So says Gregory Beran, at the ...

In a recent study published in the journal Nature Methods, a group of researchers developed a novel method called Ribonucleic Acid (RNA) High-Order Folding Prediction Plus (RhoFold+). This deep ...

Researchers have developed a powerful new method to simulate and predict how cracks form and grow in engineering materials ...

Understanding and preventing drug side effects holds a profound influence on drug development and utilization, profoundly impacting patients’ physical and mental well-being. Traditional artificial ...

Computer simulations and artificial intelligence often make significant errors when predicting the properties of new, high-performance materials, according to a new international study led by the ...

AI models outperform traditional statistics in predicting post-complete cytoreduction outcomes in ovarian cancer patients. AI's diagnostic accuracy was high for predicting overall survival and no ...

Experts are increasingly turning to machine learning to predict antibiotic resistance in pathogens. With its help, resistance ...

Investigations suggest V2P may be efficiently applied for the automated identification of causal variants in simulated and actual patient sequencing data across phenotypes.

Explore how prediction markets work, their types, real-world applications, and the benefits they offer in forecasting events ...