正在加载图片...
·710 智能系统学报 第11卷 medicine:a network-based approach to human disease[J]. [10]RUEPP A,WAEGELE B,LECHNER M,et al.CORUM: Nature reviews genetics,2011,12(1):56-68. the comprehensive resource of mammalian protein comple- [2]BADER G D,HOGUE C W V.An automated method for xes-2009[J].Nucleic acids research,2010,38 (S1): finding molecular complexes in large protein interaction net- D497-D501. works[J].BMC bioinformatics,2003,4:2. [11]ZHANG Z Y.Community structure detection in complex [3]ALTAF-UL-AMIN M,SHINBO Y,MIHARA K,et al.De- networks with partial background information J].EPL velopment and implementation of an algorithm for detection europhysics letters),2013,101(4):48005. of protein complexes in large interaction networks[J].BMC [12]ASHBURNER M,BALL C A,BLAKE J A,et al.Gene bioinformatics,2006,7:207. Ontology:tool for the unification of biology[].Nature ge- [4]KENLEY E C,CHO Y R.Detecting protein complexes and netics,2000,25(1)):25-29. functional modules from protein interaction networks:A [13]SCHAEFER C F,ANTHONY K,KRUPA S,et al.PID: graph entropy approach[]].Proteomics,2011,11(19): the pathway interaction database[J].Nucleic acids re- 3835-3844. search,2009,37(S1):D674-D679 [5]MENCHE J,SHARMA A,KITSAK M,et al.Uncovering 作者简介: disease-disease relationships through the incomplete interac- 刘光明.男,1986年生,博士研究 tome[JJ.Science,.2015,347(6224):1257601 生,主要研究方向为复杂网络、数据挖 [6]NEWMAN M E J.Fast algorithm for detecting community 掘、蛋白质功能模块。 structure in networks[J].Physical review e,2004,69(6): 066133. [7]WAGSTAFF K,CARDIE C,ROGERS S,et al.Constrain- ed k-means clustering with background knowledge [C]// 杨柳.女,1980年生,博士研究生 Proceedings of the Eighteenth International Conference on 主要研究方向为机器学习、数据挖掘。 Machine Learning.San Francisco,CA,USA:Morgan Kauf- mann Publishers Inc.,2001:577-584. [8]LEE DD,SEUNG H S.Learning the parts of objects by non-negative matrix factorization J].Nature,1999,401 (6755):788-791 高盼盼,女,1989年生,硕士研究 [9]TURANALP M E,CAN T.Discovering functional interac- 生,主要研究方向为基于药物副作用的 tion patterns in protein-protein interaction networks[J]. 分子机理的研究、数据挖掘。 BMC bioinformatics,2008,9:276.medicine: a network⁃based approach to human disease[ J]. Nature reviews genetics, 2011, 12(1): 56⁃68. [2]BADER G D, HOGUE C W V. An automated method for finding molecular complexes in large protein interaction net⁃ works[J]. BMC bioinformatics, 2003, 4: 2. [3]ALTAF⁃UL⁃AMIN M, SHINBO Y, MIHARA K, et al. De⁃ velopment and implementation of an algorithm for detection of protein complexes in large interaction networks[ J]. BMC bioinformatics, 2006, 7: 207. [4]KENLEY E C, CHO Y R. Detecting protein complexes and functional modules from protein interaction networks: A graph entropy approach [ J]. Proteomics, 2011, 11 ( 19): 3835⁃3844. [5]MENCHE J, SHARMA A, KITSAK M, et al. Uncovering disease⁃disease relationships through the incomplete interac⁃ tome[J]. Science, 2015, 347(6224): 1257601. [6]NEWMAN M E J. Fast algorithm for detecting community structure in networks[J]. Physical review e, 2004, 69(6): 066133. [7]WAGSTAFF K, CARDIE C, ROGERS S, et al. Constrain⁃ ed k⁃means clustering with background knowledge [ C] / / Proceedings of the Eighteenth International Conference on Machine Learning. San Francisco, CA, USA: Morgan Kauf⁃ mann Publishers Inc., 2001: 577⁃584. [8]LEE D D, SEUNG H S. Learning the parts of objects by non⁃negative matrix factorization [ J]. Nature, 1999, 401 (6755): 788⁃791. [9]TURANALP M E, CAN T. Discovering functional interac⁃ tion patterns in protein⁃protein interaction networks [ J ]. BMC bioinformatics, 2008, 9: 276. [10]RUEPP A, WAEGELE B, LECHNER M, et al. CORUM: the comprehensive resource of mammalian protein comple⁃ xes⁃2009[ J]. Nucleic acids research, 2010, 38 ( S1): D497⁃D501. [11] ZHANG Z Y. Community structure detection in complex networks with partial background information [ J ]. EPL (europhysics letters), 2013, 101(4): 48005. [12]ASHBURNER M, BALL C A, BLAKE J A, et al. Gene Ontology: tool for the unification of biology[J]. Nature ge⁃ netics, 2000, 25(1): 25⁃29. [13]SCHAEFER C F, ANTHONY K, KRUPA S, et al. PID: the pathway interaction database [ J]. Nucleic acids re⁃ search, 2009, 37(S 1): D674⁃D679. 作者简介: 刘光明,男,1986 年生,博士研究 生,主要研究方向为复杂网络、数据挖 掘、蛋白质功能模块。 杨柳,女,1980 年生,博士研究生, 主要研究方向为机器学习、数据挖掘。 高盼盼,女,1989 年生,硕士研究 生,主要研究方向为基于药物副作用的 分子机理的研究、数据挖掘。 ·710· 智 能 系 统 学 报 第 11 卷
<<向上翻页
©2008-现在 cucdc.com 高等教育资讯网 版权所有