Semi-supervised learning with pseudo-labeling compares favorably with large language models for regulatory sequence prediction.

Abstract excerpt

Predicting molecular processes using deep learning is a promising approach to provide biological insights for non-coding single nucleotide polymorphisms identified in genome-wide association studies. However, most deep learning methods rely on supervised learning, which requires DNA sequences associated with functional data, and whose amount is severely limited by the finite size of the human genome. Conversely,...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Algorithms
• Share to Computational Biology
• Share to Deep Learning