generative-AI

Today in AI for life science: AI-designed proteins become new tools to see inside living cells, generative models write genomes on demand, and a synthesis breakthrough finally lets labs build what AI dreams up.

Today in AI for life science: models move past static structures to predict proteins as moving ensembles, that frontier hits a data wall, and self-evolving agents repurpose drugs for rare diseases — where the wet lab both confirms and refutes.

Today in AI for life science: generative AI can finally design proficient enzymes, autonomous biofoundries close the design-build-test loop, and a census of 1,196 biology-AI models finds safeguards remain the rare exception.

Using of OpenAI’s GPT models for generating Python code from natural language to assist with bioimage analysis, providing an intuitive interface for non-programmers, while also highlighting the need for running generated code in a secure environment due to potential inaccuracies and security concerns.