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  • 统计与管理学院2017年学术报告第42

     

    【主  题】Matrix factorization for data integration in bioinformatics

    【报告人】张世华, 副研究员

    中国科学院数学与系统科学研究院

    【时  间】 2017年06月19日(星期一)16:00-17:00

    【地  点】 上海财经大学统计与管理学院大楼1208室

    【摘  要】Nonnegative matrix factorization (NMF) is a powerful technique for dimension reduction and pattern recognition. In this talk, I will survey the recent applications of NMF and its variants joint NMF in bioinformatics. Next, I will introduce some new algorithmic exploration about joint NMF and its application in RNA-protein binding prediction. Lastly, I will present a flexible NMF framework CSMF to combine data dimension reduction and differential analysis into one paradigm to simultaneously reveal common and specific patterns from data generated under interrelated biological scenarios. We demonstrate the effectiveness of CSMF with four biological applications. Extensive analysis yields novel insights into hidden combinatorial patterns embedded in these interrelated multi-modal data. Results demonstrate that CSMF is a powerful tool to uncover common and specific patterns with significant biological implications from data of interrelated biological scenarios.

    【邀请人】 刘旭