{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T19:18:29Z","timestamp":1785352709607,"version":"3.55.0"},"reference-count":214,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T00:00:00Z","timestamp":1778716800000},"content-version":"vor","delay-in-days":13,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Clinical and Translational Science Awards","award":["UM1TR004539"],"award-info":[{"award-number":["UM1TR004539"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,5,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Artificial intelligence (AI) is reshaping genomics by enabling unprecedented insights into disease mechanisms, therapeutic design, and precision medicine. This review provides a comprehensive survey of cutting-edge AI methodologies, including machine learning, deep learning (DL), natural language processing, large language models, generative frameworks, and explainable AI, and their applications across genomics. We systematically summarize how these technologies advance key domains, such as gene sequencing, variant detection, gene expression analysis, personalized medicine, and CRISPR-based genome editing. Core computational tools, benchmark datasets, and open-source frameworks supporting AI-driven genomic research are detailed. Despite remarkable progress, challenges persist in data quality, interpretability, ethical governance, and computational scalability. Integrating multi-omics data through advanced architectures, such as graph neural networks and multimodal DL promises deeper biological understanding. Emerging paradigms, e.g. synthetic genomics and digital twins, highlight AI\u2019s potential to deliver predictive and personalized healthcare.<\/jats:p>","DOI":"10.1093\/bib\/bbag229","type":"journal-article","created":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T11:35:29Z","timestamp":1777116929000},"source":"Crossref","is-referenced-by-count":4,"title":["Artificial Intelligence in genomics: a comprehensive survey of methods, resources, challenges, and prospects"],"prefix":"10.1093","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6280-7035","authenticated-orcid":false,"given":"Md","family":"Ishtyaq Mahmud","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Houston , 4226 Martin Luther King Boulevard, 77204-4005 TX,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tania","family":"Banerjee","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Houston , 4226 Martin Luther King Boulevard, 77204-4005 TX,","place":["United States"]},{"name":"Department of Information Science Technology, University of Houston , 14000 University Boulevard, 77479-0800, TX,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,5,14]]},"reference":[{"key":"2026051410042350800_ref1","doi-asserted-by":"crossref","first-page":"931","DOI":"10.1038\/nature03001","article-title":"Finishing the euchromatic sequence of the human genome","volume":"431","author":"International Human Genome Sequencing Consortium","year":"2004","journal-title":"Nature"},{"key":"2026051410042350800_ref2","article-title":"The evolution of next-generation sequencing technologies","volume-title":"High Throughput Gene Screening: Methods and Protocols","author":""},{"key":"2026051410042350800_ref3","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/3065386","article-title":"ImageNet classification with deep convolutional neural networks","volume":"60","author":"Krizhevsky","year":"2017","journal-title":"Commun ACM"},{"key":"2026051410042350800_ref4","volume-title":"Proceedings of the 12th USENIX conference on Operating Systems Design and Implementation (OSDI'16)","author":""},{"key":"2026051410042350800_ref5","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1038\/nbt.4235","article-title":"A universal SNP and small-indel variant caller using deep neural networks","volume":"36","author":"Poplin","year":"2018","journal-title":"Nat Biotechnol"},{"key":"2026051410042350800_ref6","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1038\/s41586-021-03819-2","article-title":"Highly accurate protein structure prediction with alphafold","volume":"596","author":"Jumper","year":"2021","journal-title":"Nature"},{"key":"2026051410042350800_ref7","doi-asserted-by":"crossref","first-page":"1138","DOI":"10.1126\/science.aaa1934","article-title":"Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq","volume":"347","author":"Zeisel","year":"2015","journal-title":"Science"},{"key":"2026051410042350800_ref8","first-page":"43177","article-title":"HyenaDNA: long-range genomic sequence modeling at single nucleotide resolution","volume":"36","author":"Nguyen","year":"2023","journal-title":"Adv Neural Inf Proces Syst"},{"key":"2026051410042350800_ref9","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1038\/s41592-024-02523-z","article-title":"Nucleotide transformer: building and evaluating robust foundation models for human genomics","volume":"22","author":"Dalla-Torre","year":"2025","journal-title":"Nat Methods"},{"key":"2026051410042350800_ref10","doi-asserted-by":"crossref","first-page":"1353","DOI":"10.1038\/s41551-022-00942-x","article-title":"Graph representation learning in biomedicine and healthcare","volume":"6","author":"Li","year":"2022","journal-title":"Nat Biomed Eng"},{"key":"2026051410042350800_ref11","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1038\/s41746-022-00712-8","article-title":"Multimodal machine learning in precision health: a scoping review","volume":"5","author":"Kline","year":"2022","journal-title":"NPJ Digit Med"},{"key":"2026051410042350800_ref12","doi-asserted-by":"crossref","first-page":"1255","DOI":"10.3390\/jpm12081255","article-title":"Digital twins in healthcare: is it the beginning of a new era of evidence-based medicine? 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