Single-cell analysis stands at the intersection of machine learning (ML) and biology, with advances in microfluidic technology generating massive datasets that are ideal for ML-driven discovery. But with this opportunity comes a challenge: ensuring that computational methods are evaluated fairly, reproducibly, and at scale.
That’s the mission of OpenProblems.bio, a community-driven initiative turning complex single-cell challenges into living, standardized benchmarks. Each benchmark defines tasks, datasets, metrics, and methods that are automatically executed as reproducible pipelines.
A Shared Infrastructure for Reproducible Science
Three technologies make this possible:
- OpenProblems.bio provides the community framework, curated tasks, open results, and transparent governance.
- Viash bridges the gap between scripts and pipelines, letting scientists contribute methods without needing deep workflow expertise.
- Seqera provides the scalable infrastructure to run these benchmarks across cloud and HPC environments.
At Data Intuitive, we help ensure this shared infrastructure is robust, maintainable, and reproducible, supporting the community in building pipelines that scale globally while preserving scientific transparency.
Building the Future of BioML Collaboration
OpenProblems.bio represents a new model for scientific collaboration — one where ML and bioinformatics communities come together around shared standards, transparent metrics, and open infrastructure.
By combining the strengths of Viash, Nextflow, and Seqera, the initiative connects scientific ambition with computational reality, empowering researchers to move fast without breaking reproducibility.
Read the full story on Seqera’s blog: https://hubs.la/Q03Np_H70