Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Scientists usually study the molecular machinery that controls gene expression from the perspective of a linear, two-dimensional genome—even though DNA and its bound proteins function in three ...

A mass of writhing maggots on a decomposing murder victim is not a sight for the squeamish, but for some, it is evidence. A maggot’s age and species can give essential information to forensic ...

Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average diagnosis time?

When the performance of AI models was assessed within stratified patient subgroups, such as only high-grade breast cancers or only MSI-positive tumors, accuracy fell substantially, revealing that the ...

Artificial intelligence tools are increasingly being developed to predict cancer biology directly from microscope images, ...

Read more about AI-powered peptide discovery could transform fight against drug-resistant superbugs on Devdiscourse ...

The partnership integrates high-resolution multi-omics data generation with predictive multimodal machine learning to support biopharma decision-making in neurology.

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...

LCGC International’s interview series on the evolving role of artificial intelligence (AI)/machine learning (ML) in separation science continues with Boudewijn Hollebrands from Unilever Foods R&D, ...