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February 17, 2023

Code Ocean Partners with Nature Portfolio to Launch the Open Science Library with Ready-to-Run Software from Authors in Nature Journals

NEW YORKFeb. 17, 2023 /PRNewswire/ — Code Ocean, the world’s first Reproducible Research Cloud, today announced that it has partnered with Nature Portfolio to launch a curated Open Science Library, containing research software published by authors in popular Nature journals, including Nature Methods, Nature Computational Science, Nature Biotechnology, Nature Machine Intelligence, and more. The software collection is available for use with a free account at

A subsidiary of Springer Nature, Nature Portfolio serves the research community by publishing its most significant discoveries — findings that advance knowledge and address some of the greatest challenges that we face as a society today. Its journals publish not only primary research but also reviews, critical comment, news, and analysis. “We’re thrilled to partner with Code Ocean,” said Erika Pastrana, Editorial Director, Nature Portfolio. “This unique collection of journal compute capsules will enable readers to easily re-use code associated with our publications and will support our authors to gain more visibility, boost the usage of their work, and ensure reproducibility.”

“We’re thrilled to partner with Code Ocean,” said Erika Pastrana, Editorial Director, Nature Portfolio.

Until now, life science researchers have struggled to keep pace with a growing amount of data and computational software that is not immediately reproducible and usable for future research. They often find themselves unable to quickly duplicate research results and build new science on prior experiments. Unfortunately, this reproducibility crisis slows new discoveries, because past results are difficult or impossible to reproduce — in fact, more than 70% of computational research is non-reproducible, according to an analysis by Proceedings of the National Academy of Sciences (PNAS).

Code Ocean provides a Reproducible Research Cloud for research data and computational software that empowers pharmaceutical and biotech researchers to collaborate more quickly and effectively. One of the key differentiators of Code Ocean’s approach is its Compute Capsule, which creates a software package comprising the essential triplet of any computational research experiment – code, data, and computing environment enabling researchers to reproduce, reuse, and collaborate. Capsules, input datasets and results become assets and are managed in a secure, shareable repository. This system of cloud-based Capsules automatically traces the path of research data, mapping each step in a detailed timeline, and provides full knowledge of the path a scientist took during discovery, making each stage of computation fully reproducible.

“Code Ocean addresses the creative chaos inherent in computational science by providing one end-to-end platform for data and computational research in the wet and dry lab,” said Simon Adar, Co-founder and CEO, Code Ocean. “Nature’s highly esteemed research authors publish the world’s cutting-edge computational research on the Open Science Library. This is open access to all researchers. With a library of ready-to-run research software, our joint offering will help to accelerate the speed and enhance the quality of life science research.”

“If you have to recreate from scratch the analysis code or if you have issues running the provided code, it will likely be a labor-intensive, lengthy, and risky initiative,” said Benjamin Haibe-Kains, Ph.D., Associate Professor, Medical Biophysics Department, University of Toronto. “Code Ocean totally solves tracking and reproducing analysts for researchers and increases trust in the results.”

About Code Ocean

Code Ocean makes science move faster by empowering research teams with a platform that is the central hub for research data and computational assets. Code Ocean provides a standards-based environment that organizes and controls the creative chaos, allowing researchers to collaborate more quickly, seamlessly, and effectively by preserving a record of the data and code of every result. The outcome is complete trust in your results: visibility, lineage, and exact reproducibility of every computational experiment. For more information, please visit

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