ArticleNucleic acids research2025
GENA-LM: a family of open-source foundational DNA language models for long sequences.
Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 2 of them syntheses that pooled it.
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Who cites it
74 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence for genomic science: a scoping review of concepts, architectures, applications, and open challenges.Frontiers in bioinformatics · 2026Pooled it
- A systematic review on the generative AI applications in human medical genetics.Frontiers in genetics · 2025Pooled it
- A cfDNA fragmentomics-based machine learning model for predicting treatment response and recurrence in locally advanced rectal cancer after neoadjuvant chemoradiotherapy.The journal of liquid biopsy · 2026Article
- Machine learning and statistical methods for molecular quantitative trait loci.Nature reviews. Genetics · 2026Review
- Review
- LAMBDA: a prophage detection benchmark for genomic language models.NAR genomics and bioinformatics · 2026Article
- ASPIRE: Accurate alternative splicing prediction from limited RNA sequencing data and a minimal gene set.PLoS computational biology · 2026Article
- ATACompass enables cross-species cell identity mapping for scATAC-seq without gene annotations.Cell reports methods · 2026Article
- Systematic contextual biases in SegmentNT potentially relevant to other nucleotide transformer models.Nucleic acids research · 2026Article
- Foundation models in omics research: a comprehensive survey.Briefings in bioinformatics · 2026Review
- EssTFNet: integration of adaptive time-frequency and DNA language models for interpretable human essential gene prediction.Briefings in bioinformatics · 2026Article
- Advancing bioinformatics with language models: components, applications, and perspectives.Briefings in bioinformatics · 2026Review
- Advances and challenges of splicing prediction with AI.Nature genetics · 2026Review
- TSProm: deep learning framework to predict tissue-specific regulatory logic.NAR genomics and bioinformatics · 2026Article
- Generalist biological artificial intelligence in modeling the language of life.Nature biotechnology · 2026Review
- Porcine MutBERT: a family of lightweight genomic foundation models for functional element prediction in pigs.Briefings in bioinformatics · 2026Article
- Systematic contextual biases in SegmentNT potentially relevant to other nucleotide transformer models.bioRxiv : the preprint server for biology · 2026Article
- Workflow for Fine-Tuning and Evaluating DNA Language Models for Specific Genomics Issues.Bio-protocol · 2026Article
- Deep learning for psychiatric genomics: from tools to applications.Current opinion in genetics & development · 2026Review
- Novel principles of molecular genetic mapping of the interphase genome of Drosophila melanogaster.G3 (Bethesda, Md.) · 2026Article
14 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Recent advancements in genomics, propelled by artificial intelligence, have unlocked unprecedented capabilities in interpreting genomic sequences, mitigating the need for exhaustive experimental analysis of complex, intertwined molecular processes inherent in DNA function. A significant challenge, however, resides in accurately decoding genomic sequences, which inherently involves comprehending rich contextual information dispersed across thousands of nucleotides. To address this need, we introduce GENA language model (GENA-LM), a suite of transformer-based foundational DNA language models capable of handling input lengths up to 36 000 base pairs. Notably, integrating the newly developed recurrent memory mechanism allows these models to process even larger DNA segments. We provide pre-trained versions of GENA-LM, including multispecies and taxon-specific models, demonstrating their capability for fine-tuning and addressing a spectrum of complex biological tasks with modest computational demands. While language models have already achieved significant breakthroughs in protein biology, GENA-LM showcases a similarly promising potential for reshaping the landscape of genomics and multi-omics data analysis. All models are publicly available on GitHub (https://github.com/AIRI-Institute/GENA_LM) and on HuggingFace (https://huggingface.co/AIRI-Institute). In addition, we provide a web service (https://dnalm.airi.net/) allowing user-friendly DNA annotation with GENA-LM models.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.