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- 基本信息
报告人：刘丙强 山东大学 副院长
报告题目：Inference of disease-associated microbial gene modules based on metagenomic and metatranscriptomic data
报告摘要：The identification of disease-***, the heterogeneity, high dimensionality, ***, we present IDAM, a novel computational method for disease-*** (uber-operon) and regulatory mechanisms (gene co-expression patterns) to explore gene modules associated with specific phenotypes using a mathematical graph model, without relying on prior meta-***, melanoma, type 1 diabetes mellitus, and irritable bowel syndrome and demonstrated the superior performance of IDAM in disease-***-associated microbial characteristics, and potentially pave the way for understanding the role of the microbiome in human diseases.
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