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We are announcing the Deep Origin data hub, an expansion of our R&D platform that seamlessly integrates data management, scalable data processing and AI-driven analysis. In the Deep Origin data hub, researchers can design experiments, create protocols, write experimental notes, upload raw data, perform complex analyses, create interactive visualizations, generate publication ready figures, and collaborate all in a single place. Free access to our beta is available to the first 200 users*.

In the biotech domain, extracting AI's benefits is often a challenge, as scattered, unstructured data generated by the research process stands in the way. Here we explore the common ways AI is used in biology, and what process tools you might want to consider to prepare your data for AI models and scientific analysis.

In this post, we’ll approach bioinformatics in a digestible, beginner-friendly manner, focusing on the why and how by what I believe to be the best way to learn: reproducing data from existing papers.

Building environments for interactive scientific computing with Docker

We tested the publicly available AlphaFold 3 instance and have reviewed the paper. Note that access to the full tool is not yet available and is provided only as a server with limitations. Here's what we found.