REMME & REBEAN scripts and models

We introduce two LMs, a pretrained foundation model REMME, aimed at understanding the DNA context of metagenomic reads, and the fine-tuned REBEAN for predicting the enzymatic potential encoded within the read-corresponding genes. By emphasizing function recognition over gene identification, REBEAN labels gene-encoded molecular functions of previously explored and new (orphan) sequences. Even though it was not trained to do so, REBEAN identifies the gene’s function-relevant parts. It thus expands enzymatic annotation of unassembled metagenomic reads. Here, we present novel enzymes discovered using our models, highlighting model impact on our understanding of microbial communities.Other data repo:Prabakaran, R; Bromberg, Yana (2025). EC First class predictions for metagenomic reads from Extreme environments. figshare. Dataset. https://doi.org/10.6084/m9.figshare.29286734.v1