新型基础模型整合分类层级用于肠道微生物组分析

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

研究人员开发了TaxoMFM，一个新颖的基础模型，通过整合分类层级来分析人类肠道微生物组。与使用扁平化表示的先前模型不同，TaxoMFM利用自监督学习来理解不同分类级别上的丰度模式以及组内的相对比例。该模型在TaxoGut-HPP数据集上进行了评估，该数据集包含超过100,000个微生物组样本，并涵盖了许多预测任务。TaxoMFM在预测包括结直肠癌、2型糖尿病和炎症性肠病在内的各种健康状况方面表现出有竞争力的性能，即使在零样本迁移场景下也是如此。 AI

影响该模型有望通过增进对与肠道微生物组相关的疾病的理解和预测来推动精准医疗的发展。

排序理由该集群描述了一篇详细介绍用于微生物组分析的新型基础模型的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Haochen Xue, Anastasia Godneva, Yulong Li, Qi Cao, Zhaodong Wu, Kaiyu Liang, Jionglong Su, Eran Segal, Imran Razzak · 2026-11-02 05:00

TaxoMFM: A Taxonomy-Aware Foundation Model for the Human Gut Microbiome

arXiv:2610.39316v2 Announce Type: replace Abstract: Existing gut microbiome foundation models typically use flat taxon representations, limiting their ability to exploit known taxonomic hierarchies. We introduce TaxoMFM, a microbiome foundation model that integrates taxonomic str…

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TaxoMFM: A Taxonomy-Aware Foundation Model for the Human Gut Microbiome

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