青岛大学学报（自然科学版）2024，Vol.37Issue(2)：47-54,8.DOI:10.3969/j.issn.1006-1037.2024.02.09
基于肠道菌群多模态信息融合的疾病检测方法
Multimodal Information Fusion of Gut Microbiome for Disease Detection Method
摘要
Abstract
Current methods for analyzing amplicon sequencing data that utilize Operational Taxonomic U-nits(OTU)or Amplicon Sequence Variants(ASV)can lose multimodal information from various species spectrum construction methods.An analysis was conducted on the differences in community diversity and structure between OTU and ASV datasets across four diseases.An effective approach to integrate OTU and ASV for disease characterization prediction was proposed:MDDMI(Microbiome-based Disease Detec-tion with Multimodal Information).The results indicate that MDDMI is superior to the single-mode data analysis method.关键词
图卷积神经网络/疾病预测/多模态/肠道菌群Key words
graph convolutional networks/disease prediction/multimodal/gut microbiome分类
信息技术与安全科学引用本文复制引用
刘畅,吴舜尧..基于肠道菌群多模态信息融合的疾病检测方法[J].青岛大学学报（自然科学版）,2024,37(2):47-54,8.基金项目
山东省自然科学基金(批准号:ZR2019PF012)资助 （批准号:ZR2019PF012）
山东省高等学校科技计划(批准号:J18KA356)资助. （批准号:J18KA356）
