title: Aggregation effect in microarray data analysis.
abstract: Inferring gene regulatory networks from microarray data has become a popular activity in recent years, resulting in an ever-increasing volume of publications. There are many pitfalls in network analysis that remain either unnoticed or scantily understood. A critical discussion of such pitfalls is long overdue. Here we discuss one feature of microarray data the investigators need to be aware of when embarking on a study of putative associations between elements of networks and pathways.
authors: School of Mathematical Sciences, Rochester Institute of Technology, Rochester, NY, USA.
authors: Linlin
authors: L
authors: Chen
authors: Anthony
authors: A
authors: Almudevar
authors: Lev
authors: L
authors: Klebanov
mesh_terms: D000465:Algorithms; D002138:Calibration; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D015233:Models, Statistical; D015999:Multivariate Analysis; D016011:Normal Distribution; D020411:Oligonucleotide Array Sequence Analysis / Q000592:standards*; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D013269:Stochastic Processes; D059467:Transcriptome
chemical_list: D012333:RNA, Messenger