Modular Analysis of the Probabilistic Genetic Interaction Network

【作者】 侯琳； 汤超； 王霖； 钱敏平； 李栋； 朱云平； 邓明华； 李方廷；

【Author】 Lin Hou~(1,2,4),Chao Tang~(2,5,6,7),Lin Wang Minping Qian~(1,2) DongLi~4 Yunping Zhu~(4,*),Minghua Deng~(1,2,3,*),Fangting Li~(2,8,*) 1LMAM,School of Mathematical Sciences,Peking University,Beijing 100871,China 2Center for Theoretical Biology,Peking University,Beijing 100871,China 3Center for Statistical Center,Peking University,Beijing 100871 4State Key Laboratory of Proteomics,Beijing Proteome Research Center,Beijing Institute of Radiation Medicine,Beijing 102206,China 5California Institute for Quantitative Biosciences,University of California,San Francisco,CA 94158,USA 6Department of Bioengineering and Therapeutic Sciences,University of California,San Francisco, CA 94158,USA 7Department of Biochemistry and Biophysics,University of California,San Francisco,CA 94158, USA 8School of Physics,Peking University,Beijing 100871,China

【机构】 北京大学数学科学学院； 北京大学理论生物中心； 军事医学科学院北京放射医学研究所北京蛋白质组研究中心蛋白质组国家重点实验室； California Institute for Quantitative Biosciences,University of California,San Francisco,CA 94158,USA； Department of Bioengineering and Therapeutic Sciences,University of California,San Francisco,CA 94158,USA； Department of Biochemistry and Biophysics,University of California,San Francisco,CA 94158,USA； 北京大学统计科学中心； 北京大学物理学院；

【摘要】 <正>Epistasis Miniarray Profiles(EMAP) has enabled the mapping of large-scale genetic interaction networks;however,the quantitative information of EMAP is not fully exploited since the data is usually interpreted as a discrete network through arbitrary hard threshold.To address these limitations,we更多还原