title: An approach for determining and measuring network hierarchy applied to comparing the phosphorylome and the regulome.
abstract: Many biological networks naturally form a hierarchy with a preponderance of downward information flow. In this study, we define a score to quantify the degree of hierarchy in a network and develop a simulated-annealing algorithm to maximize the hierarchical score globally over a network. We apply our algorithm to determine the hierarchical structure of the phosphorylome in detail and investigate the correlation between its hierarchy and kinase properties. We also compare it to the regulatory network, finding that the phosphorylome is more hierarchical than the regulome.
authors.affiliation: Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA. chao.cheng@dartmouth.edu.|Institute for Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, USA. chao.cheng@dartmouth.edu.|Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, USA. chao.cheng@dartmouth.edu.
authors.forename: Chao
authors.initials: C
authors.lastname: Cheng
authors.affiliation: Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA. erik.h.andrews.med@dartmouth.edu.
authors.forename: Erik
authors.initials: E
authors.lastname: Andrews
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, 260 Whitney Avenue, New Haven, CT, 06520, USA. koon-kiu.yan@yale.edu.
authors.forename: Koon-Kiu
authors.initials: KK
authors.lastname: Yan
authors.affiliation: Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA. matthew.ung@dartmouth.edu.
authors.forename: Matthew
authors.initials: M
authors.lastname: Ung
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, 260 Whitney Avenue, New Haven, CT, 06520, USA. daifeng.wang@yale.edu.
authors.forename: Daifeng
authors.initials: D
authors.lastname: Wang
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, 260 Whitney Avenue, New Haven, CT, 06520, USA. mark.gerstein@yale.edu.|Department of Molecular Biophysics and Biochemistry, Yale University, 260 Whitney Avenue, New Haven, CT, 06520, USA. mark.gerstein@yale.edu.|Department of Computer Science, Yale University, 260 Whitney Avenue, New Haven, CT, 06520, USA. mark.gerstein@yale.edu.
authors.forename: Mark
authors.initials: M
authors.lastname: Gerstein
mesh_terms: D000465:Algorithms; D053263:Gene Regulatory Networks / Q000235:genetics*; D023281:Genomics; D006801:Humans; D008954:Models, Biological; D010766:Phosphorylation / Q000235:genetics*; D015003:Yeasts / Q000235:genetics