随着分子生物学技术蓬勃发展,越来越多的肿瘤学者通过The Cancer Genome Atlas(TCGA)数据库下载高通量测序数据,运用生物信息学分析的方法,识别肿瘤免疫微环境中各种细胞的表达量,进行肿瘤浸润性免疫细胞的分析工作,但是肿瘤与免疫的相...随着分子生物学技术蓬勃发展,越来越多的肿瘤学者通过The Cancer Genome Atlas(TCGA)数据库下载高通量测序数据,运用生物信息学分析的方法,识别肿瘤免疫微环境中各种细胞的表达量,进行肿瘤浸润性免疫细胞的分析工作,但是肿瘤与免疫的相互作用往往十分复杂,临床工作人员面对庞大数据量展开分析工作仍然充满困难,基于此本文介绍一款全面分析肿瘤浸润性免疫细胞及其可视化的数据库TIMER2.0,旨在为临床研究人员轻松识别多种癌症类型与正常组织及免疫细胞浸润之间的基因组学关系,快速运用多种算法掌握肿瘤概况。展开更多
Recently,Wireless sensor networks(WSNs)have become very popular research topics which are applied to many applications.They provide pervasive computing services and techniques in various potential applications for the...Recently,Wireless sensor networks(WSNs)have become very popular research topics which are applied to many applications.They provide pervasive computing services and techniques in various potential applications for the Internet of Things(IoT).An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism(ACMDGTM)algorithm is proposed which would mitigate the problem of“hot spots”among sensors to enhance the lifetime of networks.The clustering process takes sensors’location and residual energy into consideration to elect suitable cluster heads.Furthermore,one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself.Related experimental results display that the presented method can avoid long distance communicate between sensor nodes.Furthermore,this algorithm reduces energy consumption effectively and improves package delivery rate.展开更多
文摘随着分子生物学技术蓬勃发展,越来越多的肿瘤学者通过The Cancer Genome Atlas(TCGA)数据库下载高通量测序数据,运用生物信息学分析的方法,识别肿瘤免疫微环境中各种细胞的表达量,进行肿瘤浸润性免疫细胞的分析工作,但是肿瘤与免疫的相互作用往往十分复杂,临床工作人员面对庞大数据量展开分析工作仍然充满困难,基于此本文介绍一款全面分析肿瘤浸润性免疫细胞及其可视化的数据库TIMER2.0,旨在为临床研究人员轻松识别多种癌症类型与正常组织及免疫细胞浸润之间的基因组学关系,快速运用多种算法掌握肿瘤概况。
基金This work is supported by the National Natural Science Foundation of China(61772454,61811530332,61811540410,U1836208).
文摘Recently,Wireless sensor networks(WSNs)have become very popular research topics which are applied to many applications.They provide pervasive computing services and techniques in various potential applications for the Internet of Things(IoT).An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism(ACMDGTM)algorithm is proposed which would mitigate the problem of“hot spots”among sensors to enhance the lifetime of networks.The clustering process takes sensors’location and residual energy into consideration to elect suitable cluster heads.Furthermore,one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself.Related experimental results display that the presented method can avoid long distance communicate between sensor nodes.Furthermore,this algorithm reduces energy consumption effectively and improves package delivery rate.
