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Approaches to Modeling Gene Regulatory Networks: A Gentle Introduction

  • Thomas Schlitt
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1021)

Abstract

This chapter is split into two main sections; first, I will present an introduction to gene networks. Second, I will discuss various approaches to gene network modeling which will include some examples for using different data sources. Computational modeling has been used for many different biological systems and many approaches have been developed addressing the different needs posed by the different application fields. The modeling approaches presented here are not limited to gene regulatory networks and occasionally I will present other examples.

The material covered here is an update based on several previous publications by Thomas Schlitt and Alvis Brazma (FEBS Lett 579(8),1859–1866, 2005; Philos Trans R Soc Lond B Biol Sci 361(1467), 483–494, 2006; BMC Bioinformatics 8(suppl 6), S9, 2007) that formed the foundation for a lecture on gene regulatory networks at the In Silico Systems Biology workshop series at the European Bioinformatics Institute in Hinxton.

Keywords

Gene Regulatory Network Boolean Network Differential Equation Model Part List System Biology Markup Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

I would like to thank Nicolas Le Novère, Julio Saez-Rodriguez, Vicky Schneider, and James Watson for organizing and running the excellent In Silico Systems Biology workshops. I would also like to thank my former supervisor Alvis Brazma for the introduction to gene network modeling and many interesting discussions.

References

  1. 1.
    Schlitt T, Brazma A (2005) Modelling gene networks at different organisational levels. FEBS Lett 579(8):1859–1866. doi: S0014-5793(05)00186-9[pii]10.1016/j.febslet.2005.01.073 PubMedCrossRefGoogle Scholar
  2. 2.
    Schlitt T, Brazma A (2006) Modelling in molecular biology: describing transcription regulatory networks at different scales. Philos Trans R Soc Lond B Biol Sci 361(1467):483–494. doi: E686M06225352114[pii]10.1098/rstb.2005.1806 PubMedCrossRefGoogle Scholar
  3. 3.
    Schlitt T, Brazma A (2007) Current approaches to gene regulatory network modelling. BMC Bioinformatics 8(suppl 6):S9. doi: 1471-2105-8-S6-S9[pii]10.1186/1471-2105-8-S6-S9 PubMedCrossRefGoogle Scholar
  4. 4.
    Krebs JE (2009) Lewin’s genes X, 10th edn. Jones and Bartlett, Burlington, MAGoogle Scholar
  5. 5.
    Ptashne M (1992) A genetic switch—phage lambda and higher organisms, 2nd edn. Cell Press & Blackwell Science, OxfordGoogle Scholar
  6. 6.
    Lederberg EM, Lederberg J (1953) Genetic studies of lysogenicity in Escherichia Coli. Genetics 38(1):51–64PubMedGoogle Scholar
  7. 7.
    Johnson AD, Poteete AR, Lauer G, Sauer RT, Ackers GK, Ptashne M (1981) Lambda repressor and cro–components of an efficient molecular switch. Nature 294(5838):217–223PubMedCrossRefGoogle Scholar
  8. 8.
    St-Pierre F, Endy D (2008) Determination of cell fate selection during phage lambda infection. Proc Natl Acad Sci U S A 105(52):20705–20710. doi: 0808831105[pii]10.1073/pnas.0808831105 PubMedCrossRefGoogle Scholar
  9. 9.
    Brazma A, Schlitt T (2003) Reverse engineering of gene regulatory networks: a finite state linear model. Genome Biol 4(6):P5CrossRefGoogle Scholar
  10. 10.
    Ruklisa D, Brazma A, Viksna J (2005) Reconstruction of gene regulatory networks under the Finite State Linear Model. Genome Inform 16(2):225–236PubMedGoogle Scholar
  11. 11.
    Overbeek R, Begley T, Butler RM, Choudhuri JV, Chuang HY, Cohoon M, de Crecy-Lagard V, Diaz N, Disz T, Edwards R, Fonstein M, Frank ED, Gerdes S, Glass EM, Goesmann A, Hanson A, Iwata-Reuyl D, Jensen R, Jamshidi N, Krause L, Kubal M, Larsen N, Linke B, McHardy AC, Meyer F, Neuweger H, Olsen G, Olson R, Osterman A, Portnoy V, Pusch GD, Rodionov DA, Ruckert C, Steiner J, Stevens R, Thiele I, Vassieva O, Ye Y, Zagnitko O, Vonstein V (2005) The subsystems approach to genome annotation and its use in the project to annotate 1000 genomes. Nucleic Acids Res 33(17):5691–5702PubMedCrossRefGoogle Scholar
  12. 12.
    Babu MM, Luscombe NM, Aravind L, Gerstein M, Teichmann SA (2004) Structure and evolution of transcriptional regulatory networks. Curr Opin Struct Biol 14(3):283–291PubMedCrossRefGoogle Scholar
  13. 13.
    Madan Babu M, Teichmann SA (2003) Functional determinants of transcription factors in Escherichia coli: protein families and binding sites. Trends Genet 19(2):75–79PubMedCrossRefGoogle Scholar
  14. 14.
    Koonin EV, Fedorova ND, Jackson JD, Jacobs AR, Krylov DM, Makarova KS, Mazumder R, Mekhedov SL, Nikolskaya AN, Rao BS, Rogozin IB, Smirnov S, Sorokin AV, Sverdlov AV, Vasudevan S, Wolf YI, Yin JJ, Natale DA (2004) A comprehensive evolutionary classification of proteins encoded in complete eukaryotic genomes. Genome Biol 5(2):R7PubMedCrossRefGoogle Scholar
  15. 15.
    Bornholdt S, Schuster HG (eds) (2003) Handbook of graphs and networks, 1st edn. Willey-VCH, WeinheimGoogle Scholar
  16. 16.
    Saris CG, Horvath S, van Vught PW, van Es MA, Blauw HM, Fuller TF, Langfelder P, DeYoung J, Wokke JH, Veldink JH, van den Berg LH, Ophoff RA (2009) Weighted gene co-expression network analysis of the peripheral blood from amyotrophic lateral sclerosis patients. BMC Genomics 10:405. doi: doi:1471-2164-10-405[pii]10.1186/1471-2164-10-405 PubMedCrossRefGoogle Scholar
  17. 17.
    Zhang B, Horvath S (2005) A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol 4:Article17. doi: 10.2202/1544-6115.1128 PubMedGoogle Scholar
  18. 18.
    Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9:559. doi: 1471-2105-9-559[pii]10.1186/1471-2105-9-559 PubMedCrossRefGoogle Scholar
  19. 19.
    Suderman M, Hallett M (2007) Tools for visually exploring biological networks. Bioinformatics 23(20):2651–2659. doi: btm401[pii]10.1093/bioinformatics/btm401 PubMedCrossRefGoogle Scholar
  20. 20.
    Cline MS, Smoot M, Cerami E, Kuchinsky A, Landys N, Workman C, Christmas R, Avila-Campilo I, Creech M, Gross B, Hanspers K, Isserlin R, Kelley R, Killcoyne S, Lotia S, Maere S, Morris J, Ono K, Pavlovic V, Pico AR, Vailaya A, Wang P-L, Adler A, Conklin BR, Hood L, Kuiper M, Sander C, Schmulevich I, Schwikowski B, Warner GJ, Ideker T, Bader GD (2007) Integration of biological networks and gene expression data using Cytoscape. Nat Protoc 2(10):2366–2382PubMedCrossRefGoogle Scholar
  21. 21.
    Galas DJ, Schmitz A (1978) DNAse footprinting: a simple method for the detection of protein-DNA binding specificity. Nucleic Acids Res 5(9):3157–3170PubMedCrossRefGoogle Scholar
  22. 22.
    Garner MM, Revzin A (1981) A gel electrophoresis method for quantifying the binding of proteins to specific DNA regions: application to components of the Escherichia coli lactose operon regulatory system. Nucleic Acids Res 9(13):3047–3060PubMedCrossRefGoogle Scholar
  23. 23.
    Orlando V (2000) Mapping chromosomal proteins in vivo by formaldehyde-crosslinked-chromatin immunoprecipitation. Trends Biochem Sci 25(3):99–104PubMedCrossRefGoogle Scholar
  24. 24.
    Deonier RC, Tavaré S, Waterman MS (2005) Computational genome analysis: an introduction. Springer, HeidelbergGoogle Scholar
  25. 25.
    Matys V, Fricke E, Geffers R, Gossling E, Haubrock M, Hehl R, Hornischer K, Karas D, Kel AE, Kel-Margoulis OV, Kloos DU, Land S, Lewicki-Potapov B, Michael H, Munch R, Reuter I, Rotert S, Saxel H, Scheer M, Thiele S, Wingender E (2003) TRANSFAC: transcriptional regulation, from patterns to profiles. Nucleic Acids Res 31(1):374–378PubMedCrossRefGoogle Scholar
  26. 26.
    Bryne JC, Valen E, Tang MH, Marstrand T, Winther O, da Piedade I, Krogh A, Lenhard B, Sandelin A (2008) JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update. Nucleic Acids Res 36(Database issue):D102–D106. doi: gkm955[pii]10.1093/nar/gkm955 PubMedGoogle Scholar
  27. 27.
    Brazma A, Jonassen I, Vilo J, Ukkonen E (1998) Predicting gene regulatory elements in silico on a genomic scale. Genome Res 8(11):1202–1215PubMedGoogle Scholar
  28. 28.
    Rustici G, Mata J, Kivinen K, Lio P, Penkett CJ, Burns G, Hayles J, Brazma A, Nurse P, Bahler J (2004) Periodic gene expression program of the fission yeast cell cycle. Nat Genet 36(8):809–817PubMedCrossRefGoogle Scholar
  29. 29.
    Werner T, Fessele S, Maier H, Nelson PJ (2003) Computer modeling of promoter organization as a tool to study transcriptional coregulation. FASEB J 17(10):1228–1237PubMedCrossRefGoogle Scholar
  30. 30.
    Dickmeis T, Muller F (2005) The identification and functional characterisation of conserved regulatory elements in developmental genes. Brief Funct Genomic Proteomic 3(4):332–350PubMedCrossRefGoogle Scholar
  31. 31.
    Sauer T, Shelest E, Wingender E (2006) Evaluating phylogenetic footprinting for human-rodent comparisons. Bioinformatics 22(4):430–437PubMedCrossRefGoogle Scholar
  32. 32.
    Bansal M, Califano A (2012) Genome-wide dissection of posttranscriptional and posttranslational interactions. Methods Mol Biol 786:131–149. doi: 10.1007/978-1-61779-292-2_8 PubMedCrossRefGoogle Scholar
  33. 33.
    Costanzo M, Baryshnikova A, Bellay J, Kim Y, Spear ED, Sevier CS, Ding H, Koh JL, Toufighi K, Mostafavi S, Prinz J, St Onge RP, VanderSluis B, Makhnevych T, Vizeacoumar FJ, Alizadeh S, Bahr S, Brost RL, Chen Y, Cokol M, Deshpande R, Li Z, Lin ZY, Liang W, Marback M, Paw J, San Luis BJ, Shuteriqi E, Tong AH, van Dyk N, Wallace IM, Whitney JA, Weirauch MT, Zhong G, Zhu H, Houry WA, Brudno M, Ragibizadeh S, Papp B, Pal C, Roth FP, Giaever G, Nislow C, Troyanskaya OG, Bussey H, Bader GD, Gingras AC, Morris QD, Kim PM, Kaiser CA, Myers CL, Andrews BJ, Boone C (2010) The genetic landscape of a cell. Science 327(5964):425–431. doi: 327/5964/425[pii]10.1126/science.1180823 PubMedCrossRefGoogle Scholar
  34. 34.
    Guelzim N, Bottani S, Bourgine P, Kepes F (2002) Topological and causal structure of the yeast transcriptional regulatory network. Nat Genet 31(1):60–63PubMedCrossRefGoogle Scholar
  35. 35.
    Erdös P, Rényi A (1960) On the evolution of random graphs. Publications of the Mathematical Institute of the Hungarian Academy of Sciences 17–61Google Scholar
  36. 36.
    de Silva E, Stumpf MP (2005) Complex networks and simple models in biology. J R Soc Interface 2(5):419–430PubMedCrossRefGoogle Scholar
  37. 37.
    Albert R, Jeong H, Barabasi AL (2000) Error and attack tolerance of complex networks. Nature 406(6794):378–382. doi: 10.1038/35019019 PubMedCrossRefGoogle Scholar
  38. 38.
    Albert R, Jeong H, Barabasi AL (2001) Correction: error and attack tolerance of complex networks. Nature 409(6819):542Google Scholar
  39. 39.
    Hartwell LH, Hopfield JJ, Leibler S, Murray AW (1999) From molecular to modular cell biology. Nature 402(6761 suppl):C47–C52PubMedCrossRefGoogle Scholar
  40. 40.
    Schlosser G, Wagner GP (2004) Modularity in development and evolution, 1st edn. University of Chicago Press, ChicagoGoogle Scholar
  41. 41.
    Enright AJ, Van Dongen S, Ouzounis CA (2002) An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res 30(7):1575–1584PubMedCrossRefGoogle Scholar
  42. 42.
    Frey BJ, Dueck D (2007) Clustering by passing messages between data points. Science 315(5814):972–976. doi: 1136800[pii]10.1126/science.1136800 PubMedCrossRefGoogle Scholar
  43. 43.
    Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, Alon U (2002) Network motifs: simple building blocks of complex networks. Science 298(5594):824–827PubMedCrossRefGoogle Scholar
  44. 44.
    Han JD, Bertin N, Hao T, Goldberg DS, Berriz GF, Zhang LV, Dupuy D, Walhout AJ, Cusick ME, Roth FP, Vidal M (2004) Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature 430(6995):88–93PubMedCrossRefGoogle Scholar
  45. 45.
    Park D, Park J, Park SG, Park T, Choi SS (2008) Analysis of human disease genes in the context of gene essentiality. Genomics 92(6):414–418. doi: 10.1016/j.ygeno.2008.08.001 PubMedCrossRefGoogle Scholar
  46. 46.
    Zotenko E, Mestre J, O’Leary DP, Przytycka TM (2008) Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality. PLoS Comput Biol 4(8):e1000140PubMedCrossRefGoogle Scholar
  47. 47.
    He X, Zhang J (2006) Why do hubs tend to be essential in protein networks? PLoS Genet 2(6):e88. doi: 10.1371/journal.pgen.0020088 PubMedCrossRefGoogle Scholar
  48. 48.
    Batada NN, Hurst LD, Tyers M (2006) Evolutionary and physiological importance of hub proteins. PLoS Comput Biol 2(7):e88. doi: 06-PLCB-RA-0076R2[pii]10.1371/journal.pcbi.0020088 PubMedCrossRefGoogle Scholar
  49. 49.
    Hahn MW, Kern AD (2005) Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. Mol Biol Evol 22(4):803–806. doi: msi072[pii]10.1093/molbev/msi072 PubMedCrossRefGoogle Scholar
  50. 50.
    Yu H, Greenbaum D, Xin Lu H, Zhu X, Gerstein M (2004) Genomic analysis of essentiality within protein networks. Trends Genet 20(6):227–231. doi: 10.1016/j.tig.2004.04.008 S0168952504001015[pii] PubMedCrossRefGoogle Scholar
  51. 51.
    Jeong H, Mason SP, Barabasi AL, Oltvai ZN (2001) Lethality and centrality in protein networks. Nature 411(6833):41–42PubMedCrossRefGoogle Scholar
  52. 52.
    Harbison CT, Gordon DB, Lee TI, Rinaldi NJ, Macisaac KD, Danford TW, Hannett NM, Tagne JB, Reynolds DB, Yoo J, Jennings EG, Zeitlinger J, Pokholok DK, Kellis M, Rolfe PA, Takusagawa KT, Lander ES, Gifford DK, Fraenkel E, Young RA (2004) Transcriptional regulatory code of a eukaryotic genome. Nature 431(7004):99–104PubMedCrossRefGoogle Scholar
  53. 53.
    Luscombe NM, Babu MM, Yu H, Snyder M, Teichmann SA, Gerstein M (2004) Genomic analysis of regulatory network dynamics reveals large topological changes. Nature 431(7006):308–312PubMedCrossRefGoogle Scholar
  54. 54.
    Yuh CH, Bolouri H, Davidson EH (1998) Genomic cis-regulatory logic: experimental and computational analysis of a sea urchin gene. Science 279(5358):1896–1902PubMedCrossRefGoogle Scholar
  55. 55.
    Davidson EH, Rast JP, Oliveri P, Ransick A, Calestani C, Yuh CH, Minokawa T, Amore G, Hinman V, Arenas-Mena C, Otim O, Brown CT, Livi CB, Lee PY, Revilla R, Rust AG, Pan Z, Schilstra MJ, Clarke PJ, Arnone MI, Rowen L, Cameron RA, McClay DR, Hood L, Bolouri H (2002) A genomic regulatory network for development. Science 295(5560):1669–1678PubMedCrossRefGoogle Scholar
  56. 56.
    Davidson EH, Rast JP, Oliveri P, Ransick A, Calestani C, Yuh CH, Minokawa T, Amore G, Hinman V, Arenas-Mena C, Otim O, Brown CT, Livi CB, Lee PY, Revilla R, Schilstra MJ, Clarke PJ, Rust AG, Pan Z, Arnone MI, Rowen L, Cameron RA, McClay DR, Hood L, Bolouri H (2002) A provisional regulatory gene network for specification of endomesoderm in the sea urchin embryo. Dev Biol 246(1):162–190PubMedCrossRefGoogle Scholar
  57. 57.
    Longabaugh WJ, Davidson EH, Bolouri H (2009) Visualization, documentation, analysis, and communication of large-scale gene regulatory networks. Biochim Biophys Acta 1789(4):363–374. doi: S1874-9399(08)00162-4[pii]10.1016/j.bbagrm.2008.07.014 PubMedCrossRefGoogle Scholar
  58. 58.
    Saez-Rodriguez J, Alexopoulos LG, Epperlein J, Samaga R, Lauffenburger DA, Klamt S, Sorger PK (2009) Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction. Mol Syst Biol 5:331. doi: msb200987[pii]10.1038/msb.2009.87 PubMedCrossRefGoogle Scholar
  59. 59.
    Samaga R, Saez-Rodriguez J, Alexopoulos LG, Sorger PK, Klamt S (2009) The logic of EGFR/ErbB signaling: theoretical properties and analysis of high-throughput data. PLoS Comput Biol 5(8):e1000438. doi: 10.1371/journal.pcbi.1000438 PubMedCrossRefGoogle Scholar
  60. 60.
    Klamt S, Saez-Rodriguez J, Gilles ED (2007) Structural and functional analysis of cellular networks with Cell NetAnalyzer. BMC Syst Biol 1:2. doi: 1752-0509-1-2[pii]10.1186/1752-0509-1-2 PubMedCrossRefGoogle Scholar
  61. 61.
    de Jong H (2002) Modeling and simulation of genetic regulatory systems: a literature review. J Comput Biol 9(1):67–103PubMedCrossRefGoogle Scholar
  62. 62.
    Kauffman S (1969) Homeostasis and differentiation in random genetic control networks. Nature 224(215):177–178PubMedCrossRefGoogle Scholar
  63. 63.
    Kauffman SA (1993) The origins of order, self-organization and selection in evolution. Oxford University Press, New YorkGoogle Scholar
  64. 64.
    Akutsu T, Miyano S, Kuhara S (2000) Inferring qualitative relations in genetic networks and metabolic pathways. Bioinformatics 16(8):727–734PubMedCrossRefGoogle Scholar
  65. 65.
    Albert R, Barabasi AL (2000) Dynamics of complex systems: scaling laws for the period of Boolean networks. Phys Rev Lett 84(24):5660–5663PubMedCrossRefGoogle Scholar
  66. 66.
    D’Haeseleer P, Liang S, Somogyi R (2000) Genetic network inference: from co-expression clustering to reverse engineering. Bioinformatics 16(8):707–726PubMedCrossRefGoogle Scholar
  67. 67.
    Klamt S, Saez-Rodriguez J, Lindquist JA, Simeoni L, Gilles ED (2006) A methodology for the structural and functional analysis of signaling and regulatory networks. BMC Bioinformatics 7:56PubMedCrossRefGoogle Scholar
  68. 68.
    Pandey S, Wang RS, Wilson L, Li S, Zhao Z, Gookin TE, Assmann SM, Albert R (2010) Boolean modeling of transcriptome data reveals novel modes of heterotrimeric G-protein action. Mol Syst Biol 6:372. doi: msb201028[pii]10.1038/msb.2010.28 PubMedCrossRefGoogle Scholar
  69. 69.
    Kauffman S, Peterson C, Samuelsson B, Troein C (2003) Random Boolean network models and the yeast transcriptional network. Proc Natl Acad Sci U S A 100(25):14796–14799. doi: 10.1073/pnas.2036429100 2036429100[pii] PubMedCrossRefGoogle Scholar
  70. 70.
    Kauffman S, Peterson C, Samuelsson B, Troein C (2004) Genetic networks with canalyzing Boolean rules are always stable. Proc Natl Acad Sci U S A 101(49):17102–17107. doi: 0407783101[pii]10.1073/pnas.0407783101 PubMedCrossRefGoogle Scholar
  71. 71.
    Albert I, Thakar J, Li S, Zhang R, Albert R (2008) Boolean network simulations for life scientists. Source Code Biol Med 3:16. doi: 1751-0473-3-16[pii]10.1186/1751-0473-3-16 PubMedCrossRefGoogle Scholar
  72. 72.
    Saadatpour A, Albert I, Albert R (2010) Attractor analysis of asynchronous Boolean models of signal transduction networks. J Theor Biol 266(4):641–656. doi: S0022-5193(10)00379-6[pii]10.1016/j.jtbi.2010.07.022 PubMedCrossRefGoogle Scholar
  73. 73.
    Thomas R (1973) Boolean formalization of genetic control circuits. J Theor Biol 42(3):563–585PubMedCrossRefGoogle Scholar
  74. 74.
    Thomas R (1991) Regulatory networks seen as asynchronous automata: a logical description. J Theor Biol 153:1–23CrossRefGoogle Scholar
  75. 75.
    Naldi A, Carneiro J, Chaouiya C, Thieffry D (2010) Diversity and plasticity of Th cell types predicted from regulatory network modelling. PLoS Comput Biol 6(9):e1000912. doi: e1000912[pii]10.1371/journal.pcbi.1000912 PubMedCrossRefGoogle Scholar
  76. 76.
    Naldi A, Berenguier D, Faure A, Lopez F, Thieffry D, Chaouiya C (2009) Logical modelling of regulatory networks with GINsim 2.3. Biosystems 97(2):134–139. doi: S0303-2647(09)00066-5[pii]10.1016/j.biosystems.2009.04.008 PubMedCrossRefGoogle Scholar
  77. 77.
    Petri CA, Reisig W (2008) Petri net. Scholarpedia 3(4):6477CrossRefGoogle Scholar
  78. 78.
    Koch I, Reisig W, Schreiber F (eds) (2011) Modeling in systems biology: the Petri net approach. Computational biology, 1st edn. Springer, London. doi: 10.1007/978-1-84996-474-6 Google Scholar
  79. 79.
    Banks R, Khomenko V, Steggles LJ (2011) Modeling genetic regulatory networks. In: Koch I, Reisig W, Schreiber F (eds) Modeling in systems biology: the Petri net approach, 1st edn. Springer, London. doi: 10.1007/978-1-84996-474-6 Google Scholar
  80. 80.
    D’Haeseleer P, Wen X, Fuhrman S, Somogyi R (1999) Linear modeling of mRNA expression levels during CNS development and injury. Pac Symp Biocomput 41–52 http://www.ncbi.nlm.nih.gov/pubmed/10380184
  81. 81.
    van Someren EP, Wessels LF, Reinders MJ (2000) Linear modeling of genetic networks from experimental data. Proc Int Conf Intell Syst Mol Biol 8:355–366PubMedGoogle Scholar
  82. 82.
    von Dassow G, Meir E, Munro EM, Odell GM (2000) The segment polarity network is a robust developmental module. Nature 406(6792):188–192CrossRefGoogle Scholar
  83. 83.
    Lequieu J, Chakrabarti A, Nayak S, Varner JD (2011) Computational modeling and analysis of insulin induced eukaryotic translation initiation. PLoS Comput Biol 7(11):e1002263. doi: 10.1371/journal.pcbi.1002263 PCOMPBIOL-D-11-00832[pii] PubMedCrossRefGoogle Scholar
  84. 84.
    Weisse AY, Middleton RH, Huisinga W (2010) Quantifying uncertainty, variability and likelihood for ordinary differential equation models. BMC Syst Biol 4:144. doi: 1752-0509-4-144[pii]10.1186/1752-0509-4-144 PubMedCrossRefGoogle Scholar
  85. 85.
    Mendes P, Kell DB (2001) MEG (Model Extender for Gepasi): a program for the modelling of complex, heterogeneous, cellular systems. Bioinformatics 17(3):288–289PubMedCrossRefGoogle Scholar
  86. 86.
    Mendes P (1997) Biochemistry by numbers: simulation of biochemical pathways with Gepasi 3. Trends Biochem Sci 22(9):361–363. doi: S0968000497011031[pii] PubMedCrossRefGoogle Scholar
  87. 87.
    Funahashi A, Matsuoka Y, Jouraku A, Morohashi M, Kikuchi N, Kitano H (2008) Cell Designer 3.5: a versatile modeling tool for biochemical networks. Proc IEEE 96(8):1254–1265CrossRefGoogle Scholar
  88. 88.
    Takahashi K, Ishikawa N, Sadamoto Y, Sasamoto H, Ohta S, Shiozawa A, Miyoshi F, Naito Y, Nakayama Y, Tomita M (2003) E-Cell 2: multi-platform E-Cell simulation system. Bioinformatics 19(13):1727–1729PubMedCrossRefGoogle Scholar
  89. 89.
    McAdams HH, Shapiro L (1995) Circuit simulation of genetic networks. Science 269(5224):650–656PubMedCrossRefGoogle Scholar
  90. 90.
    Friedman N, Linial M, Nachman I, Pe’er D (2000) Using Bayesian networks to analyze expression data. J Comput Biol 7(3–4):601–620PubMedCrossRefGoogle Scholar
  91. 91.
    Murphy K, Mian S (1999) Modelling gene expression data using dynamic Bayesian networks. Technical report, U.C. Berkeley, Department of Computer ScienceGoogle Scholar
  92. 92.
    Pournara I, Wernisch L (2004) Reconstruction of gene networks using Bayesian learning and manipulation experiments. Bioinformatics 20(17):2934–2942PubMedCrossRefGoogle Scholar
  93. 93.
    Titsias MK, Honkela A, Lawrence ND, Rattray M (2012) Identifying targets of multiple co-regulating transcription factors from expression time-series by Bayesian model comparison. BMC Syst Biol 6(1):53.doi: 1752-0509-6-53[pii]10.1186/1752-0509-6-53 PubMedCrossRefGoogle Scholar
  94. 94.
    Pe’er D (2005) Bayesian network analysis of signaling networks: a primer. Sci STKE 2005(281):pl4PubMedGoogle Scholar
  95. 95.
    Shmulevich I, Dougherty ER, Kim S, Zhang W (2002) Probabilistic Boolean Networks: a rule-based uncertainty model for gene regulatory networks. Bioinformatics 18(2):261–274PubMedCrossRefGoogle Scholar
  96. 96.
    Matsuno H, Doi A, Nagasaki M, Miyano S (2000) Hybrid Petri net representation of gene regulatory network. Pac Symp Biocomput 341–352 http://www.ncbi.nlm.nih.gov/pubmed/?term=10902182
  97. 97.
    Goss PJ, Peccoud J (1998) Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets. Proc Natl Acad Sci U S A 95(12):6750–6755PubMedCrossRefGoogle Scholar
  98. 98.
    Ruths D, Muller M, Tseng JT, Nakhleh L, Ram PT (2008) The signaling petri net-based simulator: a non-parametric strategy for characterizing the dynamics of cell-specific signaling networks. PLoS Comput Biol 4(2):e1000005. doi: 10.1371/journal.pcbi.1000005 PubMedCrossRefGoogle Scholar
  99. 99.
    Arkin A, Ross J, McAdams HH (1998) Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells. Genetics 149(4):1633–1648PubMedGoogle Scholar
  100. 100.
    McAdams HH, Arkin A (1997) Stochastic mechanisms in gene expression. Proc Natl Acad Sci U S A 94(3):814–819PubMedCrossRefGoogle Scholar
  101. 101.
    McAdams HH, Arkin A (1999) It’s a noisy business! Genetic regulation at the nanomolar scale. Trends Genet 15(2):65–69PubMedCrossRefGoogle Scholar
  102. 102.
    Theocharidis A, van Dongen S, Enright AJ, Freeman TC (2009) Network visualization and analysis of gene expression data using BioLayout Express(3D). Nat Protoc 4(10):1535–1550. doi: nprot.2009.177[pii]10.1038/nprot.2009.177 PubMedCrossRefGoogle Scholar
  103. 103.
    Albert R, Barabasi AL (2002) Statistical mechanics of complex networks. Rev Mod Phys 74(1):47–97CrossRefGoogle Scholar
  104. 104.
    Barabasi A-L (2007) Network medicine—from obesity to the “diseasome”. N Engl J Med 357(4):404–407. doi: 10.1056/NEJMe078114 PubMedCrossRefGoogle Scholar
  105. 105.
    Dewey TG (2002) From microarrays to networks: mining expression time series. Drug Discov Today 7(20 Suppl):S170–S175PubMedCrossRefGoogle Scholar
  106. 106.
    Friedman N (2004) Inferring cellular networks using probabilistic graphical models. Science 303(5659):799–805PubMedCrossRefGoogle Scholar
  107. 107.
    Huber W, Carrey VJ, Long L, Falcon S, Gentleman R (2007) Graphs in molecular biology. BMC Bioinformatics 8(suppl 6):S8PubMedCrossRefGoogle Scholar
  108. 108.
    Kitano H (2002) Computational systems biology. Nature 420(6912):206–210PubMedCrossRefGoogle Scholar
  109. 109.
    Moore JH, Boczko EM, Summar ML (2005) Connecting the dots between genes, biochemistry, and disease susceptibility: systems biology modeling in human genetics. Mol Genet Metab 84(2):104–111PubMedCrossRefGoogle Scholar
  110. 110.
    van Someren EP, Wessels LF, Backer E, Reinders MJ (2002) Genetic network modeling. Pharmacogenomics 3(4):507–525PubMedCrossRefGoogle Scholar
  111. 111.
    Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC, Kitano H, Arkin AP, Bornstein BJ, Bray D, Cornish-Bowden A, Cuellar AA, Dronov S, Gilles ED, Ginkel M, Gor V, Goryanin II, Hedley WJ, Hodgman TC, Hofmeyr JH, Hunter PJ, Juty NS, Kasberger JL, Kremling A, Kummer U, Le Novere N, Loew LM, Lucio D, Mendes P, Minch E, Mjolsness ED, Nakayama Y, Nelson MR, Nielsen PF, Sakurada T, Schaff JC, Shapiro BE, Shimizu TS, Spence HD, Stelling J, Takahashi K, Tomita M, Wagner J, Wang J (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19(4):524–531PubMedCrossRefGoogle Scholar
  112. 112.
    Levine M, Tjian R (2003) Transcription regulation and animal diversity. Nature 424(6945):147–151. doi: 10.1038/nature01763 nature01763[pii] PubMedCrossRefGoogle Scholar
  113. 113.
    Lee TI, Rinaldi NJ, Robert F, Odom DT, Bar-Joseph Z, Gerber GK, Hannett NM, Harbison CT, Thompson CM, Simon I, Zeitlinger J, Jennings EG, Murray HL, Gordon DB, Ren B, Wyrick JJ, Tagne JB, Volkert TL, Fraenkel E, Gifford DK, Young RA (2002) Transcriptional regulatory networks in Saccharomyces cerevisiae. Science 298(5594):799–804PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2013

Authors and Affiliations

  • Thomas Schlitt
    • 1
  1. 1.Department of Medical and Molecular GeneticsKing’s College LondonLondonUK

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