Safety and security are one of the biggest areas of concern with any container-managed research application and, according to industry reports  is slowing adoption of this technology that otherwise has many benefits such as improved shareability, traceability, and reproducibility and facilitates collaboration. At Code Ocean keeping our Compute Capsules™ both safe and secure has […]
Creating an Essential Research Collaboration Environment with R Studio Today’s high-throughput biomedical research techniques and intensive interdisciplinary collaborations – especially between biologists and computational researchers – require tools and infrastructure that are able to deal with biological big data. Computational research faces costly and time-consuming challenges, specifically Reproducibility of analyses – different computing environments and
Code Ocean App Panels and Shiny Apps The interdisciplinary nature of computational biology demands rapid, reliable sharing of analyses to enable collaborative, reproducible research between individuals and teams. Increasingly, conventional methods of sharing, e.g. PDFs or Powerpoint slides are too limited for conveying the complexity of information. Complex analyses require interactive formats The main issue
Jupyter Notebooks have become exceedingly popular in computational biology because of their ability to combine code, images and text into a single document. Adding detailed as well as easy to understand descriptions of a computational workflow is very helpful when the team has knowledge gaps, where members have different levels of coding experience and skills.