ArticleNature communications2023
Multilingual translation for zero-shot biomedical classification using BioTranslator.
Article in Nature communications, 2023. 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.
- Evaluating the Utilities of Foundation Models in Single-Cell Data Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Predicting drug-perturbed transcriptional responses using multi-conditional diffusion transformer.Quantitative biology (Beijing, China) · 2026Article
- Construction of waste-to-resource knowledge graph for industrial symbiosis identification using large language models.Nature communications · 2025Article
- Ab-initio amino acid sequence design from protein text description with ProtDAT.Nature communications · 2025Article
- Multimodal zero-shot learning of previously unseen epitranscriptomes from RNA-seq data.Briefings in bioinformatics · 2025Article
- Discovery of diverse and high-quality mRNA capping enzymes through a language model-enabled platform.Science advances · 2025Article
- A review of large language models and autonomous agents in chemistry.Chemical science · 2025Review
- Review
- Scaling up single-cell RNA-seq data analysis with CellBridge workflow.Bioinformatics (Oxford, England) · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Existing annotation paradigms rely on controlled vocabularies, where each data instance is classified into one term from a predefined set of controlled vocabularies. This paradigm restricts the analysis to concepts that are known and well-characterized. Here, we present the novel multilingual translation method BioTranslator to address this problem. BioTranslator takes a user-written textual description of a new concept and then translates this description to a non-text biological data instance. The key idea of BioTranslator is to develop a multilingual translation framework, where multiple modalities of biological data are all translated to text. We demonstrate how BioTranslator enables the identification of novel cell types using only a textual description and how BioTranslator can be further generalized to protein function prediction and drug target identification. Our tool frees scientists from limiting their analyses within predefined controlled vocabularies, enabling them to interact with biological data using free text.
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Registered trials
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