insights from industryJeff HawkinsCEOQuantum-SiIn this interview, NewsMedical speaks with Jeff Hawkins, CEO of Quantum-Si, about the challenges of conventional proteomic methods, as well as how ...

Researchers headed by a team at the Centre for Genomic Regulation, Barcelona Institute of Science and Technology and at the Wellcome Sanger Institute have developed an AI tool that they say has made a ...

Researchers developed a new machine learning method that, given a relevant amino acid sequence, can automatically predict the location of a protein in any human cell line down to the single-cell level ...

This year’s Lasker Basic Medical Research Award recognizes the contributions of Demis Hassabis and John Jumper for their invention of the AlphaFold artificial intelligence (AI) system, which predicts ...

Machine learning (ML) and other AI- based computational tools have proven their prowess at predicting real-world protein structures. AlphaFold 2, an algorithm developed by scientists at DeepMind that ...

Proteoforms, the diverse molecular variants of proteins, are key to understanding cellular functions, disease mechanisms, and biomarker discovery in proteomics.

The process of protein identification typically begins with a bottom-up approach, where proteins are enzymatically digested—most commonly with trypsin—into smaller peptides. These peptides are ...