Lin Wang's research while affiliated with Capital University of Economics and Business, Be and other places

... Multiple web-based tools allow differential expression analysis and visualization of user-supplied gene expression data. Some representative tools include MetaOmics [5], degust [6], START [7], o-miner [8], iDEP [9], IRIS-EDA [10], ExpressViz [11] and eVITTA [12]. Galaxy, a widely-used cloud-based bioinformatics workbench, provides convenient access to many commonly used analysis tools [13]. ...

... Li (2002) examined these dynamic correlation changes (referred to as liquid association in his paper) in canonical pathways using microarray gene expression data from a model organism, Saccharomyces cerevisiae. For a typical genomic study, a pathway-based or a genome-wide screening strategy can be implemented as presented in several studies to effectively identify potential dynamic correlation changes (Dawson and Kendziorski, 2012;Gunderson and Ho, 2014;Wang et al., 2017;Yu, 2018;Kinzy et al., 2019). Li's study and other studies since then have evidently established its biological validity and popularized it to be a useful tool for analyzing genomic data (Li, 2002;Ho et al., 2007;Zhang et al., 2007;Ho et al., 2011;Wang et al., 2013;Khayer et al., 2017;Wang et al., 2017;Xu et al., 2017;Ai et al., 2019;Kong and Yu, 2019;Wen et al., 2020). ...

... Since its development, its use has become exponentially widespread and allows integrating network parameters with genetic information from microarray datasets and, more recently, from RNA sequencing experiments [18][19][20]. It should be noted that variations or methods other than WGCNA have also been developed, such as Differential Co-expression Analysis or metaDCN [21], THD-Module Extractor [22], Diffcoex [23], and module differential analysis for weighted gene co-expression network (MODA) [24]. However, WGCNA remains by far the most commonly used in numerous research fields. ...