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利用大语言模型对基因型数据进行知识驱动的特征选择与工程设计

Knowledge-Driven Feature Selection and Engineering for Genotype Data with Large Language Models.

作者信息

Lee Joseph, Yang Shu, Baik Jae Young, Liu Xiaoxi, Tan Zhen, Li Dawei, Wen Zixuan, Hou Bojian, Duong-Tran Duy, Chen Tianlong, Shen Li

机构信息

Unversity of Pennsylvania, Philadelphia, USA.

RIKEN, Yokohama, Japan.

出版信息

ArXiv. 2025 Apr 16:arXiv:2410.01795v2.

PMID:40321944
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12047900/
Abstract

FreeForm, FreeForm https://github.com/PennShenLab/FREEFORM.

摘要

自由形式，自由形式 https://github.com/PennShenLab/FREEFORM。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcde/12047900/88cd17fec6f5/nihpp-2410.01795v2-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcde/12047900/09dd3ad46fad/nihpp-2410.01795v2-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcde/12047900/3215f4f4c9a4/nihpp-2410.01795v2-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcde/12047900/cbc9e7a3e92a/nihpp-2410.01795v2-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcde/12047900/bdabfad2a128/nihpp-2410.01795v2-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcde/12047900/88cd17fec6f5/nihpp-2410.01795v2-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcde/12047900/09dd3ad46fad/nihpp-2410.01795v2-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcde/12047900/3215f4f4c9a4/nihpp-2410.01795v2-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcde/12047900/cbc9e7a3e92a/nihpp-2410.01795v2-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcde/12047900/bdabfad2a128/nihpp-2410.01795v2-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcde/12047900/88cd17fec6f5/nihpp-2410.01795v2-f0005.jpg

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本文引用的文献

1
GeneAgent: self-verification language agent for gene-set analysis using domain databases.基因智能体：使用领域数据库进行基因集分析的自我验证语言智能体。
Nat Methods. 2025 Jul 28. doi: 10.1038/s41592-025-02748-6.
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Large language models surpass human experts in predicting neuroscience results.大语言模型在预测神经科学结果方面超越了人类专家。
Nat Hum Behav. 2025 Feb;9(2):305-315. doi: 10.1038/s41562-024-02046-9. Epub 2024 Nov 27.
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Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis.在单细胞RNA测序分析中评估GPT-4用于细胞类型注释
Nat Methods. 2024 Aug;21(8):1462-1465. doi: 10.1038/s41592-024-02235-4. Epub 2024 Mar 25.
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GeneGPT: augmenting large language models with domain tools for improved access to biomedical information.GeneGPT：利用领域工具增强大型语言模型，以改善对生物医学信息的访问。
Bioinformatics. 2024 Feb 1;40(2). doi: 10.1093/bioinformatics/btae075.
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Harnessing large language models (LLMs) for candidate gene prioritization and selection.利用大型语言模型（LLMs）进行候选基因优先级排序和选择。
J Transl Med. 2023 Oct 16;21(1):728. doi: 10.1186/s12967-023-04576-8.
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Large language models encode clinical knowledge.大语言模型编码临床知识。
Nature. 2023 Aug;620(7972):172-180. doi: 10.1038/s41586-023-06291-2. Epub 2023 Jul 12.
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Machine learning for predicting phenotype from genotype and environment.用于从基因型和环境预测表型的机器学习。
Curr Opin Biotechnol. 2023 Feb;79:102853. doi: 10.1016/j.copbio.2022.102853. Epub 2022 Dec 2.
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A Review of Feature Selection Methods for Machine Learning-Based Disease Risk Prediction.基于机器学习的疾病风险预测的特征选择方法综述
Front Bioinform. 2022 Jun 27;2:927312. doi: 10.3389/fbinf.2022.927312. eCollection 2022.
9
Human genotype-to-phenotype predictions: Boosting accuracy with nonlinear models.人类基因型到表型的预测：利用非线性模型提高准确性。
PLoS One. 2022 Aug 31;17(8):e0273293. doi: 10.1371/journal.pone.0273293. eCollection 2022.
10
Genetic prediction of complex traits with polygenic scores: a statistical review.基于多基因评分的复杂性状遗传预测：统计述评。
Trends Genet. 2021 Nov;37(11):995-1011. doi: 10.1016/j.tig.2021.06.004. Epub 2021 Jul 6.