Preparing samples for proteomics has traditionally required a time-consuming and error-prone multi-step workflow that, according to literature, causes 75 percent of the overall variability in proteomics data
New deep learning software for analyzing the choreography of protein movement removes the need for expert human intervention and opens up the field to more labs worldwide
Researchers introduce an optimized and integrated interaction proteomics protocol to allow rapid identification of protein-protein interactions and more