Science

Open-source workflow makes spatial proteomics easier to use

Read full article at source ↗

Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 23/10/2026, 16:25:25 UTC.

Briefings

Fabian Coscia's team published an open-source workflow called OpenDVP in Nature Methods that enables scientists to spatially map thousands of proteins within cells while maintaining tissue context. This tool simplifies the process of Deep Visual Proteomics, allowing for easier adaptation and scaling of spatial mapping techniques.

Key points

• OpenDVP is an open-source workflow published in Nature Methods by Fabian Coscia and colleagues.
• The tool allows spatial mapping of thousands of proteins inside cells while preserving tissue context.

Context

Deep Visual Proteomics (DVP) is a technique for mapping protein locations within cells. OpenDVP simplifies this complex workflow, making it more accessible for researchers to adapt and scale for spatial mapping.

Limitations

The evidence is limited to a single published article from October 2026. No additional data, experimental results, or user feedback are provided to verify the tool's performance or limitations.

Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 23/10/2026, 16:26:42 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.

View archived briefing on IPFS
bafybeihb5mtt5oyulxaykrel6ivbccci2qxdpydeh6pryqk3ehmtdjcqn4