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Researchers developed the DRIVE method, which analyzes shared segments of the genome to identify undiagnosed cases of Long QT syndrome. The study highlights the potential for better detection of rare genetic variants in larger populations.

Researchers identified CO2's complex interactions with poly(ethylenimine) sorbents, crucial for Direct Air Capture technology. The findings show CO2 both catalyzes oxidation and reduces polymer mobility.

The SPOT model uses AI to predict the substrates that specific transport proteins can carry. SPOT offers a promising approach for enhancing substrate identification, which could benefit biotechnology and drug development.

A new study from the University of Copenhagen shows that AI can help women with improved treatment by scanning for irregular-looking cells to give better risk assessment.

Researchers have found that the impact of drugs on bacteria is often less pronounced when they are part of a community, due to cross-protection strategies.

A team at the University of Missouri has created Cryo2Struct, an AI program that automates the determination of large protein structures from cryo-electron microscopy data. This allows for better understanding of protein interactions.

Researchers have utilized machine learning and genomics to identify genetic traits in Vibrio cholerae linked to severe cholera symptoms. Their findings could lead to better treatments and preventive measures.

A team created a computational workflow for analyzing metabolomics data, applied to pollutants in Southern California seawater. The tool is user-friendly for both beginners and experts, facilitating faster understanding of ocean pollution.

A new generative AI model can make it easier to determine the structure of powdered crystals in X-ray crystallography.

A recent study suggests doctors and pharmacists treating people with blood thinners can reduce the rate of inappropriate dosing using an electronic patient management system, subsequently reducing the occurrence of blood clots and strokes.