Integration of statistical models and visualization tools to characterize microRNA networks influencing cancer

James Karnia, K. Delfino, M. Villamil, G. Caetano-Anollés, S. Rodriguez-Zas
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Abstract

Gene expression microarray experiments can be used to infer the topology of co-expression networks between genes in the immune-system pathways. Immune-system pathways are highly dimensional, including numerous gene nodes and edges connecting nodes. A bioinformatics strategy to infer and confirm gene co-expression networks was developed and applied to two major immune-system pathways. In total, 182 and 356 co-expression profiles between pairs of genes were identified in the NOD-like and B-cell receptor signaling pathways. The distinct distribution of the sign of the relationships among the pathways offered additional insights into the network.
整合统计模型和可视化工具表征影响癌症的microRNA网络
基因表达微阵列实验可用于推断免疫系统通路中基因间共表达网络的拓扑结构。免疫系统通路是高度多维的,包括许多基因节点和连接节点的边缘。一种推断和确认基因共表达网络的生物信息学策略被开发并应用于两种主要的免疫系统途径。在nod样细胞和b细胞受体信号通路中,共鉴定出182和356个基因对之间的共表达谱。通路之间关系符号的独特分布提供了对网络的额外见解。
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