Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
University of Missouri researchers have released the world's largest collection of protein models with quality assessment—a ...
With MassiveFold, scientists have unlocked AlphaFold's full potential, making high-confidence protein predictions faster and more accessible, fueling breakthroughs in biology and drug discovery. Brief ...
This review provides an overview of traditional and modern methods for protein structure prediction and their characteristics and introduces the groundbreaking network features of the AlphaFold family ...
Today (September 21), the Lasker Foundation announced this year’s award winners. John Jumper, a computational biologist at DeepMind, and Demis Hassabis, cofounder and CEO at DeepMind, were awarded the ...
Master proteomics database searching. Learn how algorithms match mass spectra to sequences and optimize identification.
Researchers present BioEmu – a new AI model that rapidly and accurately predicts the full range of shapes a protein can adopt, offering a faster, cheaper alternative to traditional molecular ...
A new artificial intelligence-driven pipeline developed in a collaborative research combines protein structure prediction, sequence design, and ...
Analysis from Moffitt Cancer Center has shown that DNA-derived protein epiScores measured in blood prior to treatment can ...
Real-time and in-line accurate measuring of protein (monoclonal antibody, or mAb) concentration has been shown across a wide dynamic range (0–135 g/L) through the ...
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