title: The Local Edge Machine: inference of dynamic models of gene regulation.
abstract: We present a novel approach, the Local Edge Machine, for the inference of regulatory interactions directly from time-series gene expression data. We demonstrate its performance, robustness, and scalability on in silico datasets with varying behaviors, sizes, and degrees of complexity. Moreover, we demonstrate its ability to incorporate biological prior information and make informative predictions on a well-characterized in vivo system using data from budding yeast that have been synchronized in the cell cycle. Finally, we use an atlas of transcription data in a mammalian circadian system to illustrate how the method can be used for discovery in the context of large complex networks.
authors.affiliation: Department of Mathematics and Statistics, UNC Charlotte, 9201 University City Blvd., Charlotte, 28269, NC, USA. kmcgoff1@uncc.edu.
authors.forename: Kevin A
authors.initials: KA
authors.lastname: McGoff
authors.affiliation: Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Guo
authors.affiliation: Department of Mathematics, Duke University, Durham, NC, USA.
authors.forename: Anastasia
authors.initials: A
authors.lastname: Deckard
authors.affiliation: Department of Biology, Duke University, Durham, NC, USA.
authors.forename: Christina M
authors.initials: CM
authors.lastname: Kelliher
authors.affiliation: Department of Biology, Duke University, Durham, NC, USA.
authors.forename: Adam R
authors.initials: AR
authors.lastname: Leman
authors.affiliation: Department of Molecular and Cellular Physiology, University of Cincinnati, Cincinnati, OH, USA.
authors.forename: Lauren J
authors.initials: LJ
authors.lastname: Francey
authors.affiliation: Department of Molecular and Cellular Physiology, University of Cincinnati, Cincinnati, OH, USA.
authors.forename: John B
authors.initials: JB
authors.lastname: Hogenesch
authors.affiliation: Department of Biology, Duke University, Durham, NC, USA.
authors.forename: Steven B
authors.initials: SB
authors.lastname: Haase
authors.affiliation: Department of Mathematics, Duke University, Durham, NC, USA.
authors.forename: John L
authors.initials: JL
authors.lastname: Harer
mesh_terms: D000818:Animals; D002453:Cell Cycle / Q000235:genetics; D002940:Circadian Rhythm / Q000235:genetics; D003198:Computer Simulation; D030541:Databases, Genetic; D005786:Gene Expression Regulation / Q000235:genetics*; D053263:Gene Regulatory Networks / Q000235:genetics*; D006801:Humans; D051379:Mice; D012441:Saccharomyces cerevisiae / Q000235:genetics; D014158:Transcription, Genetic
keywords: Gene regulatory networks; Inference; Time series