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

Cardiovascular disease (CVD) remains the primary cause of death in most industrialized and developing nations. The prevention of CVD depends on its timely diagnosis to initiation of cardioprotective ...

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, ...

Machine-learning platform enables signal peptide-informed discovery of small molecules that selectively inhibit protein secretion allowing for the degradation of disease-related proteins at the point ...

Real-time proteomics tools enable comprehensive proteome coverage, instant quality control, and adaptive acquisition during experiments. Advances in machine learning are transforming proteomics ...

Revealed core proteomics instrument during US HUPO 2026 following successful field evaluation at the Buck Institute for ...

Expression proteomics determines where and when proteins are expressed and measures their quantities. This qualitative and quantitative approach can compare protein expression across conditions, such ...

Explore how proteomics supports pre-symptomatic disease detection, from mass spectrometry advances to multi-omics models and clinical validation challenges.

Plants are constantly exposed to a wide array of biotic and abiotic stresses in their natural environments, posing ...