Automatic modeling of signaling pathways by network flow model

Journal of Bioinformatics and Computational Biology

Volumn 7, Issue 2, 2009, Pages 309-322

  Zhao, X ing Ming ^a,b,c,d   Wang, Rui Sheng ^e   Chen, Luonan ^a,b,d,e   Aihara, Kazuyuki ^a,d  

^a SHANGHAI UNIVERSITY   (China)

^b JAPAN SCIENCE AND TECHNOLOGY AGENCY   (Japan)

^c INSTITUTE OF INTELLIGENT MACHINES   (China)

^d INSTITUTE OF INDUSTRIAL SCIENCE   (Japan)

^e OSAKA SANGYO UNIVERSITY   (Japan)

Author keywords

Mixed integer linear programming; Network flow model; Protein protein interaction; Signaling pathway

Indexed keywords

MITOGEN ACTIVATED PROTEIN KINASE; PHEROMONE;

AUTOMATION; CONFERENCE PAPER; FUNGUS GROWTH; LINEAR SYSTEM; PROTEIN DATABASE; PROTEIN PROTEIN INTERACTION; SIGNAL TRANSDUCTION; STATISTICAL ANALYSIS; STATISTICAL MODEL;

COMPUTER SIMULATION; MODELS, BIOLOGICAL; PROTEIN INTERACTION MAPPING; PROTEOME; SIGNAL TRANSDUCTION;

EID: 65449175659     PISSN: 02197200     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219720009004138     Document Type: Conference Paper

References (22)

1. Scott J, Ideker T, Karp RM, Sharan R, Efficient algorithms for detecting signaling pathways in protein interaction networks, J Comput Biol 13:133-144, 2006.
2. Steffen M, Petti A, Aach J, D'haeseleer P, Church G, Automated modelling of signal transduction networks, BMC Bioinformatics 3:34, 2002.
3. Liu Y, Zhao H, A computational approach for ordering signal transduction pathway components from genomics and proteomics data, BMC Bioinformatics 5:158, 2004.
4. Arga KY, Önsan Z, Kiidar B, Ölgen K, Nielsen J, Understanding signaling in yeast: Insights from network analysis, Biotechnol Bioeng 97:1246-1258, 2007.
5. Bebek G, Yang J, Pathfinder: Mining signal transduction pathway segments from protein-protein interaction networks, BMC Bioinformatics 8 335, 2007.
6. Zhao XM, Wang RS, Chen L, Aihara K, Uncovering signal transduction networks from high-throughput data by integer linear programming, Nucl Acids Res 36:e48, 2008.
7. Zhao XM, Wang RS, Chen L, Aihara K, Automatic modeling of signal pathways from protein-protein interaction networks, Proceedings of the 6th Asia Pacific Bioinformatics Conference, volume 6 of Series on Advances in Bioinformartics and Computational Biology, pp. 287-296, Imperial college press, 2008.
8. Bader J, Chaudhuri A, Rothberg J, Chant J, Gaining confidence in high-throughput protein interaction networks, Nature Biotechnol 22:78-85, 2003.
9. Deng M, Sun F, Chen T, Assessment of the reliability of protein-protein interactions and protein function prediction, In: Proceedings of the 8th Pacific Symposium on Biocomputing, 140-151, Lihue, Hawaii, 2003
10. von Mering C, Krause R, Snel B, Cornell M, Oliver SG, Fields S, Bork P, Comparative assessment of large-scale data sets of protein-protein interactions, Nature 417:399-403, 2002.
11. Sharan R, Suthram S, Kelley RM, Kuhn T, McCuine S, Uetz P, Sittler T, Karp RM, Ideker T, Conserved patterns of protein interaction in multiple species, Proc Natl Acad Sci USA 102:1974-1979, 2005.
12. Wang L, Xu Y, Haplotype inference by maximum parsimony, Bioinformatics 19:1773-1780, 2003.
13. Tobias H, Andor L, Robert F, Helgi B, Genetic algorithm for large-scale maximum parsimony phylogenetic analysis of proteins, Biochem Biophys Acta 1725:19-29, 2005.
14. Xenarios I, Salwnski L, Duan XJ, Higney P, Kim SM, Eisenberg D, DIP, the database of interacting proteins: A research tool for studying cellular networks of protein interactions, Nucleic Acids Res 30 303-305, 2002.
15. Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki T, Hirakawa M, From genomics to chemical genomics: New developments in KEGG, Nucleic Acids Res 34 (Database issue):D354-357, 2006.
16. Hirano H, Tanaka K, Ozaki K, Imamura H, Kohno H, Hihara T, Kameyama T, Hotta K, Arisawa M, Watanabe T, Qadota H, Ohya Y, Takai Y, ROM7/BEM4 encodes a novel protein that interacts with the Rho1p small GTP-binding protein in Saccharomyces cerevisiae, Mol Cell Biol 16 4396-4403, 1996.
17. Mack D, Nishimura K, Dennehey BK, Arbogast T, Parkinson J, Toh-e A, Pringle JR, Bender A, Matsui Y, Identification of the bud emergence gene BEM4 and its interactions with rho-type GTPases in Saccharomyces cerevisiae, Mol Cell Biol 16:4387-4395, 1996.
18. Askree SH, Yehuda T, Smolikov S, Gurevich R, Hawk J, Coker C, Krauskopf A, Kupiec M, McEachern MJ, From the cover: A genome-wide screen for Saccharomyces cerevisiae deletion mutants that affect telomere length, Proc Natl Acad Sci USA 101:8658-8663, 2004.
19. Mewes HW, Amid C, Arnold R, Frishman D, Guldener U, Mannhaupt G, Munsterkotter M, Pagel P, Strack N, Stumpflen V, Warfsmann J, Ruepp A, MIPS: Analysis and annotation of proteins from whole genomes, Nucleic Acids Res 32 (Database issue):D41-44, 2004.
20. Oehlen LJ, Cross FR, Potential regulation of ste20 function by the cln1-cdc28 and cln2-cdc28 cyclin-dependent protein kinases, J Biol Chem 273:25089-25097, 1998.
21. Oehlen LJ, Cross FR, G1 cyclins CLN1 and CLN2 repress the mating factor response pathway at Start in the yeast cell cycle, Genes Dev 8 1058-1070, 1994.
22. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G, Gene ontology: Tool for the unification of biology. The gene ontology consortium, Nat Genet 25:25-29, 2000.