Recent advances in deep learning and language models for studying the microbiome
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 use...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2024.1494474/full |
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| author | Binghao Yan Yunbi Nam Lingyao Li Rebecca A. Deek Hongzhe Li Siyuan Ma |
| author_facet | Binghao Yan Yunbi Nam Lingyao Li Rebecca A. Deek Hongzhe Li Siyuan Ma |
| author_sort | Binghao Yan |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-68401cc9cabc4bf19a9aa0b552203616 |
| institution | Kabale University |
| issn | 1664-8021 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj-art-68401cc9cabc4bf19a9aa0b5522036162025-01-07T06:46:03ZengFrontiers Media S.A.Frontiers in Genetics1664-80212025-01-011510.3389/fgene.2024.14944741494474Recent advances in deep learning and language models for studying the microbiomeBinghao Yan0Yunbi Nam1Lingyao Li2Rebecca A. Deek3Hongzhe Li4Siyuan Ma5Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United StatesDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United StatesSchool of Information, University of South Florida, Tampa, FL, United StatesDepartment of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, PA, United StatesDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United StatesDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United StatesRecent 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.https://www.frontiersin.org/articles/10.3389/fgene.2024.1494474/fullmicrobiomeviromeartificial intelligencelarge language modelstransformerattention |
| spellingShingle | Binghao Yan Yunbi Nam Lingyao Li Rebecca A. Deek Hongzhe Li Siyuan Ma Recent advances in deep learning and language models for studying the microbiome Frontiers in Genetics microbiome virome artificial intelligence large language models transformer attention |
| title | Recent advances in deep learning and language models for studying the microbiome |
| title_full | Recent advances in deep learning and language models for studying the microbiome |
| title_fullStr | Recent advances in deep learning and language models for studying the microbiome |
| title_full_unstemmed | Recent advances in deep learning and language models for studying the microbiome |
| title_short | Recent advances in deep learning and language models for studying the microbiome |
| title_sort | recent advances in deep learning and language models for studying the microbiome |
| topic | microbiome virome artificial intelligence large language models transformer attention |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2024.1494474/full |
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