Computational biology and bioinformatics

Scalable, reproducible computational research for biotech and pharma

Code Ocean helps computational teams provision compute, set up environments, develop analysis, scale powerful pipelines, and automatically create a reproducible, traceable record of their work.

Trusted by hundreds of computational scientists and bioinformaticians:

Most computational research relies on costly, time-consuming manual workflows and custom systems.

Code Ocean makes it easy to provision, scale, collaborate, and reproduce computational scientific research.

Provision compute, launch cloud workstations

Set up new environments with built-in automation while Code Ocean generates your Dockerfile in the background. Attach data of any size, develop in your preferred IDE and language, then deploy to the cloud in one click.

Drag and drop to build bioinformatics pipelines

Drag and drop different capsules to build Pipelines, while Code Ocean generates Nextflow in the background (or import from nf-core). Adjust compute resource for each step, then run automatically on AWS Batch.

Trace all your results, then reproduce and share your work

See the provenance of all results with the Lineage Graph. All development is tracked with Git, every asset can be shared with role-based access control. No lock-in: export anything, at any time, and run it anywhere else.

Code Ocean runs on Compute Capsules

Compute Capsules are a versionable, traceable, reproducible containerization of the code, data, and environments used in computational research, as well as the result data they produce. They automate environment setup, have compute management built in, and can be shared with others to co-develop or clone and adapt.
Computational Reproducibility

Who is Code Ocean for?

Computational Scientists

Computational Scientists

Start and scale every step of computational work with built-in automations, cloud workstations, and cloud provisioning. 
IT & Engineering

IT & Engineering

Avoid technical debt, improve data architecture, and lower the support burden for your computational teams.
Research Leadership

Research Leadership

Faster onboarding, scientific reproducibility, and an immutable system-of-record for the entire IP lifecycle.
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