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雄激素受体在乳腺癌中的生物信息学分析
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作者 李兵 杜岗 Wang Jinhua 《山西中医学院学报》 2017年第3期60-63,66,共5页
目的:通过数据挖掘探讨雄激素受体(AR)在乳腺癌中发病的机制,探索协同表达基因网络中的潜在干预靶点和信号通路。方法:分别从TCGA数据库和NCBI数据库中下载了两个独立的乳腺癌基因表达谱数据,筛选出AR的关联基因,使用Cytoscape平台中的C... 目的:通过数据挖掘探讨雄激素受体(AR)在乳腺癌中发病的机制,探索协同表达基因网络中的潜在干预靶点和信号通路。方法:分别从TCGA数据库和NCBI数据库中下载了两个独立的乳腺癌基因表达谱数据,筛选出AR的关联基因,使用Cytoscape平台中的Clue Go插件对这些基因进行生物信息学分析。结果:以Pearson相关系数>0.40或<-0.40为阈值,共发现21个基因与AR有强的相关性,其中负相关4个,正相关17个;同时发现基因MLPH,SYT17,PIP,ALCAM,TOX3在既往文献报道中较少,可以成为下一步的研究方向。GO功能分析提示AR及其关联基因与上皮细胞分化、细胞形态改变、细胞内的类固醇激素受体信号通路等有关。结论:AR在乳腺癌作用中的信号通路和分子机制复杂,基于乳腺癌的数据挖掘可以为乳腺癌的个体化诊断和治疗提供科学依据。 展开更多
关键词 乳腺癌 雄激素受体 生物信息学
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Multicriteria Optimization of Cellular Networks
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作者 Roman Statnikov Josef Matusov +1 位作者 Kirill Pyankov Alexander Statnikov 《Open Journal of Optimization》 2013年第3期53-60,共8页
When designing modern cellular networks, it is challenging to account for many contradictory criteria and constantly changing external conditions of the networks (e.g., traffic). We need to solve multicriteria problem... When designing modern cellular networks, it is challenging to account for many contradictory criteria and constantly changing external conditions of the networks (e.g., traffic). We need to solve multicriteria problems with high-dimensional vectors of parameters. A prerequisite to solution of these problems is correct determination of the feasible solution set, which is directly related to the statement of optimization problem. This is a major challenge in all multicriteria engineering optimization problems and represents significant difficulties for the expert. In this paper, we show how to define the feasible solution set for cellular network optimal design problems and thus answer the fundamental question of where to search for optimal solutions in such problems. We use the Parameter Space Investigation (PSI) method implemented in the Multicriteria Optimization and Vector Identification (MOVI) software system and apply it to a mathematical model of cellular network. In addition to developing methodology for stating and solving the problem of multicriteria optimization of cellular network, we have found that 1) defining the feasible solution set is directly related to the correct statement of the optimization problem, 2) once the feasible solution set has been determined, the criteria convolution can be applied to find the optimal solution in the feasible solution set, 3) it is possible to perform online tuning of the cellular network parameters. 展开更多
关键词 Feasible Solution SET PARETO Optimal Solutions PARAMETER Space Investigation (PSI) Method CELLULAR Networks MULTICRITERIA Problems
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