An interdisciplinary approach in teaching RNA secondary structure prediction to first-year undergraduate students using an automated deep learning RNA 3D model prediction tool.

ABSTRACT: The use of artificial intelligence (AI) in biologics drug design is interlaced into the fabric of the drug discovery pipeline for many in the biotechnology industry. The use of AI tools in RNA therapeutic drug design has gained traction in recent years to develop more effective therapeutics in a short period of time, revolutionizing rapid-response therapeutics. Indeed, machine learning (ML) and deep learning (DL) are streamlining RNA therapeutic design in ways we never thought were possible just a decade ago. These advances are accompanied by a plethora of new AI tools for drug design that continue to barrage the research space at unprecedented speed. As biology educators, we bear the responsibility for keeping up with technological advances in the biotechnology space, as it is up to us to

SUBMITTER: Bhattacharjee K 

PROVIDER: S-EPMC12687630 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature