Open-source workflow makes spatial proteomics easier to use
Fabian Coscia and his team have published in Nature Methods an open-source workflow that makes Deep Visual Proteomics easier to use, adapt and scale. OpenDVP enables scientists to spatially map thousands of proteins inside cells and their cellular environments, while preserving their tissue context.
Image: Phys.org
Fabian Coscia and his team have published in Nature Methods an open-source workflow that makes Deep Visual Proteomics easier to use, adapt and scale. OpenDVP enables scientists to spatially map thousands of proteins inside cells and their cellular environments, while preserving their tissue context.
Originally published at Phys.org
