
The leading open source orchestrator for containerized, data-intensive pipelines on any infrastructure at any scale. Built by @SeqeraLabs
Barcelona | New York | London
Joined January 2014
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🎥 All the talks from the #NextflowSummit are now available to watch on-demand. Catch up on sessions from 50+ speakers, including @Roche, @Boehringer, @Lonza, @MyriadGenetics, @Benchling, @NASAGeneLab, @SeqeraLabs, and more. ▶️ Watch now: hubs.la/Q04C2lgF0
Attending #AIDDD2026 in Boston next week? Come and learn about Nextflow Frontier: a closed-loop, recursive AI system with full in silico validation to solve the unsolvable. hubs.la/Q04BT2S80
🇺🇸 We’re attending #AIDDD2026 in Boston, Oct 27–29!🎤 Don't miss our talk on Nextflow Frontier, the recursive, closed-loop discovery system built to tackle the unsolved problems in life sciences. Event details: hubs.la/Q04BT2S80
Nextflow retweeted
Most AI tools start every conversation from scratch. Co-Scientist starts with full context: your pipelines, runs, code, compute and data.✨Join us Nov 4 to see how that context now extends into interactive analysis with Studios. 🔗 Register: hubs.la/Q04BK3tV0
Nextflow retweeted
2 days, 18 projects, 60+ participants 🇪🇸 Last week in Barcelona, the @nextflowio community gathered for the @nf_core hackathon plus two hands-on training workshops.📸Check out the photos: hubs.la/Q04BHv720. Share your favorite moments with #NextflowSummit
Thanks to everyone who joined us for the @nf_core Hackathon in Barcelona last week.🤩18 projects, socks, rubber duck prizes, networking, and more! 📸Check out the photo gallery and share your favorite moments with #NextflowSummit: hubs.la/Q04BHv720
And the first rubber duck has been awarded for finding the most sock stickers in the sock hunt! 🦆🧦#NextflowSummit
🌐 Introducing Nextflow Global Cache: a shared caching layer that reuses tasks across runs, pipelines, and projects. If a task with the same inputs and script has already run anywhere in your workspace, Nextflow restores its outputs instead of rerunning it.
→ Lower compute costs, with far fewer tasks to run
→ Faster results, since cached tasks finish instantly
→ Less storage, with identical outputs stored once
→ Rename, refactor, and switch pipelines without losing cached work
♻️ No pipeline code changes needed. Compute once, reuse everywhere. 📚 Read the blog: hubs.la/Q04zM8R60


















