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  • 统计与管理学院2017年学术报告第23

     

    【主  题】Integrating multidimensional omics data for cancer prognosis

    【报告人】马双鸽, 教授

    Yale University

    【时  间】 2017年05月09日(星期二)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】Prognosis is of essential interest in cancer research. Multiple types of omics measurements – including mRNA gene expression, methylation, copy number variation, SNP, and others – have been implicated in cancer prognosis. The analysis of multidimensional omics data is challenging because of the high data dimensionality and, more importantly, because of the interconnections between different units of the same type of measurement and between different types of omics measurements. In our study, we have developed novel regularization based methods, effectively integrated multidimensional data, and constructed prognosis models. It is shown that integrating multidimensional data can lead to biological discoveries missed by the analysis of one dimensional data and superior prognosis models.

    【邀请人】 周勇