Hartl, C.L., Ramaswami, G., Pembroke, W.G.et al.Coexpression network architecture reveals the brain-wide and multiregional basis of disease susceptibility.Nat Neurosci24, 1313–1323 (2021). https://doi.org/10.1038/s41593-021-00887-5 ...
We used the network to predict the functions of poorly-characterized human genes, and provided some experimental support. Examining genes implicated in disease, we found that , a diabetes susceptibility gene, interacts with , which affects glucose transport. Genes predisposing to the same diseases ...
方法/步骤 1 根据基因在样本中的信号表达值，利用基因间的相互作用（相关系数）来拟合基因的无标度网络关系，构建基因间的共表达网络，结果样式如图。点：图中每个圆点代表一个基因。2 颜色：对于两分组（例如实验组和对照组），红色点为上调基因，蓝色为下调基因，对于多分组（例如 组1，组2，组3），由于差异基...
PPI network通常是从蛋白质互作数据库，比如HPRD/DIP等，提取全部或感兴趣的互作蛋白质对，然后使用网络...
A large variety of differential coexpression analysis methods have been developed, such as the Log Ratio of Connections11, Average Specific Connection12, Weighted Gene Coexpression Network Analysis (WGCNA)13, Differential Coexpression profile (DCp)14, Differential Coexpression enrichment (DCe)14, ...
coexpression network for cerebellum BRAINEACAlejandro, Caceres
The ZmRoot coexpression network proved to be the strongest input, discovering genes for 15 of the 17 elements (absent in Ni and Rb) for a total of 335 HPO genes, ranging from 1 to 126 per trait 4. 讨论 5. 方法 5.1 共表达网络的构建与质控(Construction and quality control of coexpressio...
Thus, we applied a correlation network model to identify the coexpressed genes and to study the impact of miRNA-142 overexpression on this network. Combining multiple sources of knowledge is useful to infer meaningful relationships in systems biology. We applied coexpression model on the data ...
By using the Hamming-Ipsen-Mikhailov (HIM) metric to quantify network differences, the effectiveness of the DTW-MIC approach is demonstrated on a set of four synthetic and one transcriptomic datasets, also in comparison to TimeDelay ARACNE and Transfer Entropy. 展开 ...
picking invertebrates such as shrimp/insects from the soft lake bottom [40].C. horeiis the most specialised fry-eater in the Tropheini with a terminal mouth andL. dardenniiis an omnivore [57]. We used weighted gene coexpression network analysis (WGCNA) to identify major coexpression modules...