ArticleQuantitative biology (Beijing, China)2024
Foundation models for bioinformatics.
Article in Quantitative biology (Beijing, China), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Artificial intelligence in plant salt stress research: from predictive models to multi-omics integration.Journal of experimental botany · 2026Review
- Applications of large-scale artificial intelligence models in bioinformatics.Quantitative biology (Beijing, China) · 2026Review
- Transformative advances in single-cell omics: a comprehensive review of foundation models, multimodal integration and computational ecosystems.Journal of translational medicine · 2025Review
- Streamline automated biomedical discoveries with agentic bioinformatics.Briefings in bioinformatics · 2025Review
- CellMemory: hierarchical interpretation of out-of-distribution cells using bottlenecked transformer.Genome biology · 2025Article
- Foundation models in bioinformatics.National science review · 2025Review
- Small, Open-Source Text-Embedding Models as Substitutes to OpenAI Models for Gene Analysis.bioRxiv : the preprint server for biology · 2025Article
- Small, open-source text-embedding models as substitutes to OpenAI models for gene analysis.Computational and structural biotechnology journal · 2025Article
- Foundation models for bioinformatics.Quantitative biology (Beijing, China) · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transformer-based foundation models such as ChatGPTs have revolutionized our daily life and affected many fields including bioinformatics. In this perspective, we first discuss about the direct application of textual foundation models on bioinformatics tasks, focusing on how to make the most out of canonical large language models and mitigate their inherent flaws. Meanwhile, we go through the transformer-based, bioinformatics-tailored foundation models for both sequence and non-sequence data. In particular, we envision the further development directions as well as challenges for bioinformatics foundation models.
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Registered trials
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