title: Top-down network analysis to drive bottom-up modeling of physiological processes.
abstract: Top-down analyses in systems biology can automatically find correlations among genes and proteins in large-scale datasets. However, it is often difficult to design experiments from these results. In contrast, bottom-up approaches painstakingly craft detailed models that can be simulated computationally to suggest wet lab experiments. However, developing the models is a manual process that can take many years. These approaches have largely been developed independently. We present LINKER, an efficient and automated data-driven method that can analyze molecular interactomes to propose extensions to models that can be simulated. LINKER combines teleporting random walks and k-shortest path computations to discover connections from a source protein to a set of proteins collectively involved in a particular cellular process. We evaluate the efficacy of LINKER by applying it to a well-known dynamic model of the cell division cycle in Saccharomyces cerevisiae. Compared to other state-of-the-art methods, subnetworks computed by LINKER are heavily enriched in Gene Ontology (GO) terms relevant to the cell cycle. Finally, we highlight how networks computed by LINKER elucidate the role of a protein kinase (Cdc5) in the mitotic exit network of a dynamic model of the cell cycle.
authors: Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, USA.
authors: Christopher L
authors: CL
authors: Poirel
authors: Richard R
authors: RR
authors: Rodrigues
authors: Katherine C
authors: KC
authors: Chen
authors: John J
authors: JJ
authors: Tyson
authors: T M
authors: TM
authors: Murali
mesh_terms: D002453:Cell Cycle / Q000502:physiology*; D018797:Cell Cycle Proteins / Q000378:metabolism*; D015966:Gene Expression Regulation, Fungal / Q000502:physiology*; D008954:Models, Biological; D017346:Protein Serine-Threonine Kinases / Q000378:metabolism*; D012441:Saccharomyces cerevisiae / Q000502:physiology*; D029701:Saccharomyces cerevisiae Proteins / Q000378:metabolism*
chemical_list: D018797:Cell Cycle Proteins; D029701:Saccharomyces cerevisiae Proteins; D017346:Protein Serine-Threonine Kinases; C081927:CDC5 protein, S cerevisiae
references: Nucleic Acids Res. 2011 Jan;39(Database issue):D136-40
references: 20972212
references: PLoS Comput Biol. 2010 Aug 19;6(8):
references: 20808879
references: Nat Rev Genet. 2011 Jan;12(1):56-68
references: 21164525
references: Nat Genet. 2009 Mar;41(3):316-23
references: 19234470
references: PLoS Comput Biol. 2011 Sep;7(9):e1002164
references: 21966263
references: Sci Signal. 2010 Dec 21;3(153):rs4
references: 21177495
references: Nat Rev Mol Cell Biol. 2006 Mar;7(3):198-210
references: 16496022
references: Nature. 1999 Jan 14;397(6715):168-71
references: 9923680
references: PLoS Comput Biol. 2010 Jan 15;6(1):e1000641
references: 20090828
references: Proc Natl Acad Sci U S A. 2002 Apr 16;99(8):5436-41
references: 11959999
references: Genome Biol. 2011;12(4):R39
references: 21492431
references: Curr Biol. 2001 May 15;11(10):784-8
references: 11378390
references: Nucleic Acids Res. 2010 Jun;38(11):3523-32
references: 20172960
references: Mol Syst Biol. 2009;5:248
references: 19293828
references: Bioinformatics. 2008 Jul 1;24(13):i223-31
references: 18586718
references: PLoS Comput Biol. 2010 Feb 26;6(2):e1000692
references: 20195502
references: Mol Biol Cell. 2004 Aug;15(8):3841-62
references: 15169868
references: Proc Natl Acad Sci U S A. 2011 Jan 11;108(2):882-7
references: 21187432
references: Genetics. 1998 Aug;149(4):1633-48
references: 9691025
references: Sci Signal. 2009 Jul 28;2(81):ra40
references: 19638617
references: Nucleic Acids Res. 2011 Jan;39(Database issue):D698-704
references: 21071413
references: PLoS Comput Biol. 2012;8(5):e1002511
references: 22615549
references: Bioinformatics. 2010 Apr 15;26(8):1057-63
references: 20185403
references: Science. 2002 Jul 19;297(5580):395-400
references: 12089449
references: Nature. 2004 May 6;429(6987):92-6
references: 15129285