ArticleAging2023
Precious1GPT: multimodal transformer-based transfer learning for aging clock development and feature importance analysis for aging and age-related disease target discovery.
Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Target identification and assessment in the era of AI.Nature reviews. Drug discovery · 2026Review
- The Evolving Landscape of Clinical Aging Clocks: From Epigenetic to Multi-Omics Integration.Aging cell · 2026Review
- Deep Learning-Enabled Multi-Omics Integration: A New Frontier in Precise Drug Target Discovery.Biology · 2026Review
- EWAS Open Platform 2026: a deeply integrated resource for epigenome-wide association studies.Nucleic acids research · 2026Article
- Artificial intelligence approaches in biological age prediction: current status and challenges.British journal of biomedical science · 2026Review
- AI-aided identification of dual-purpose therapeutic targets PRPF19 and MAPK9 in hepatocellular carcinoma and cellular senescence.npj aging · 2025Article
- The impact of artificial intelligence on biomarker discovery.Emerging topics in life sciences · 2025Article
- DoliClock: a lipid-based aging clock reveals accelerated aging in neurological disorders.Aging · 2025Article
- LLMs and AI Life Models for Traditional Chinese Medicine-derived Geroprotector Formulation.Aging and disease · 2025Article
- Deep learning and generative artificial intelligence in aging research and healthy longevity medicine.Aging · 2025Review
- Insights to aging prediction with AI based epigenetic clocks.Epigenomics · 2025Review
- Multimodal Transformers and Their Applications in Drug Target Discovery for Aging and Age-Related Diseases.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024Review
- Article
- PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery.Journal of chemical information and modeling · 2024Article
- Causality-enriched epigenetic age uncouples damage and adaptation.Nature aging · 2024Article
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Authors and funding
15 authors.
Funding
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Abstract
Aging is a complex and multifactorial process that increases the risk of various age-related diseases and there are many aging clocks that can accurately predict chronological age, mortality, and health status. These clocks are disconnected and are rarely fit for therapeutic target discovery. In this study, we propose a novel approach to multimodal aging clock we call Precious1GPT utilizing methylation and transcriptomic data for interpretable age prediction and target discovery developed using a transformer-based model and transfer learning for case-control classification. While the accuracy of the multimodal transformer is lower within each individual data type compared to the state of art specialized aging clocks based on methylation or transcriptomic data separately it may have higher practical utility for target discovery. This method provides the ability to discover novel therapeutic targets that hypothetically may be able to reverse or accelerate biological age providing a pathway for therapeutic drug discovery and validation using the aging clock. In addition, we provide a list of promising targets annotated using the PandaOmics industrial target discovery platform.
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