【摘 要】
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Integration of multi-view datasets which are comprised of heterogeneous sources or different representations is challenging to understand the subtle and complex relationship among data samples.Data in
【出 处】
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第二届中国计算机学会生物信息学会议
论文部分内容阅读
Integration of multi-view datasets which are comprised of heterogeneous sources or different representations is challenging to understand the subtle and complex relationship among data samples.Data integration methods are needed to combine efficiently the complementary information of multiple data types to construct a comprehensive view of underlying data.Here,we propose a fast and robust framework(RSNMF)based on symmetric nonnegative matrix factorization(SNMF)and similarity network fusion(SNF)for clustering human microbiome data including functional,metabolic and phylogenetic profiles from Human Microbiome Plan.
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