The most visible impact of AI seems to be in coding, but it could also be poised to disrupt other hard sciences.

Key opportunities in the protein labeling market include increasing demand for site-specific tags in proteomics and drug development, the rise of AI tools for protein structure prediction, and the ...

The intrinsically disordered proteins (IDPs) do not attain a stable secondary or tertiary structure and rapidly change their conformation, making structure prediction particularly challenging. These ...

As biological data volume continues to grow, sequence-based AI is poised to become the dominant discovery layer across pharma ...

Physical interactions between proteins influence anything from cell signaling and growth to immune responses, so the ability to control these interactions is of great interest to biologists.

In a new study published in GEN’s sister peer-review journal, GEN Biotechnology, titled, “Exploring Structure-Function Relationships in Engineered Receptor Performance Using Computational Structure ...

A domestic research team has developed an ultra-fast analysis technology capable of simultaneously tracking the evolutionary process of proteins ...

A Seoul National University research team has developed an ultra-fast analysis technology capable of tracking the protein ...

Google DeepMind released AlphaGenome on January 28, an AI model that predicts how DNA sequences translate into biological functions, processing up to one million base-pairs at once and outperforming ...