title: Analyzing mRNA and microRNA co-expression profiles to identify pathways and their potential regulators in ER+ and ER- breast tumors.
abstract: Transcription factors and microRNAs are both considered pivotal regulators of gene expression. Numerous computational methods have been developed to predict their targets. These methods, although powerful, provide a static snapshot of how genes may be regulated by transcription factors and microRNAs. We propose a method that combines these prediction data with co-expression analysis and a supervised learning algorithm to determine the main regulators in different pathways of ER+ and ER- tumors.
authors.affiliation: Department of Bioengineering, University of Illinois, Chicago MC063, Chicago, IL60607, USA. lhuang7@uic.edu
authors.forename: Lei
authors.initials: L
authors.lastname: Huang
authors.forename: Damian
authors.initials: D
authors.lastname: Roqueiro
authors.forename: Yang
authors.initials: Y
authors.lastname: Dai
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics / Q000378:metabolism*; D003198:Computer Simulation; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics*; D006801:Humans; D035683:MicroRNAs / Q000378:metabolism*; D008954:Models, Biological; D012333:RNA, Messenger / Q000378:metabolism*; D011960:Receptors, Estrogen / Q000235:genetics / Q000378:metabolism*; D015398:Signal Transduction / Q000235:genetics*; D014157:Transcription Factors / Q000235:genetics
chemical_list: D035683:MicroRNAs; D012333:RNA, Messenger; D011960:Receptors, Estrogen; D014157:Transcription Factors