AUTHOR=Yan Binghao , Nam Yunbi , Li Lingyao , Deek Rebecca A. , Li Hongzhe , Ma Siyuan 

TITLE=Recent advances in deep learning and language models for studying the microbiome

JOURNAL=Frontiers in Genetics

VOLUME=Volume 15 - 2024

YEAR=2025

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2024.1494474

DOI=10.3389/fgene.2024.1494474

ISSN=1664-8021

ABSTRACT=Recent advancements in deep learning, particularly large language models (LLMs), made a significant impact on how researchers study microbiome and metagenomics data. Microbial protein and genomic sequences, like natural languages, form a language of life, enabling the adoption of LLMs to extract useful insights from complex microbial ecologies. In this paper, we review applications of deep learning and language models in analyzing microbiome and metagenomics data. We focus on problem formulations, necessary datasets, and the integration of language modeling techniques. We provide an extensive overview of protein/genomic language modeling and their contributions to microbiome studies. We also discuss applications such as novel viromics language modeling, biosynthetic gene cluster prediction, and knowledge integration for metagenomics studies.