Presented on April 10th 2024 by Yunha Hwang

Abstract:
Deciphering the relationship between a gene and its genomic context is fundamental to understanding and engineering biological systems. We trained an unsupervised genomic language model (gLM) on the metagenomic corpus to learn the latent functional and regulatory relationships between genes. gLM presents an effective approach to generate functional hypotheses and uncover novel interactions across the metagenomic functional “dark matter”