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Volumn 16, Issue 3, 2015, Pages 146-158

Quantitative and logic modelling of molecular and gene networks

Author keywords

[No Author keywords available]

Indexed keywords

BIOENGINEERING; DATA MINING; GENE REGULATORY NETWORK; KINETICS; MATHEMATICAL MODEL; MOLECULAR GENETICS; MOLECULAR MODEL; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; REVIEW; SYNTHETIC BIOLOGY; ANIMAL; BIOLOGICAL MODEL; COMPUTER PROGRAM; HUMAN; STATISTICAL MODEL; SYSTEMS BIOLOGY;

EID: 84923687677     PISSN: 14710056     EISSN: 14710064     Source Type: Journal    
DOI: 10.1038/nrg3885     Document Type: Review
Times cited : (360)

References (145)
  • 1
    • 0027231876 scopus 로고
    • Computer simulation of the phosphorylation cascade controlling bacterial chemotaxis
    • Bray, D., Bourret, R. & Simon, M. Computer simulation of the phosphorylation cascade controlling bacterial chemotaxis. Mol. Biol. Cell 4, 482-469 (1993).
    • (1993) Mol. Biol. Cell , vol.4 , pp. 482-469
    • Bray, D.1    Bourret, R.2    Simon, M.3
  • 3
    • 84877315835 scopus 로고    scopus 로고
    • A community-driven global reconstruction of human metabolism
    • Thiele, I. et al. A community-driven global reconstruction of human metabolism. Nature Biotech. 31, 419-425 (2013).
    • (2013) Nature Biotech. , vol.31 , pp. 419-425
    • Thiele, I.1
  • 4
    • 84864258618 scopus 로고    scopus 로고
    • A whole-cell computational model predicts phenotype from genotype
    • Karr, J. R. et al. A whole-cell computational model predicts phenotype from genotype. Cell 150, 389-401 (2012).
    • (2012) Cell , vol.150 , pp. 389-401
    • Karr, J.R.1
  • 5
    • 84901262468 scopus 로고    scopus 로고
    • Integrated metabolic spatial-temporal model for the prediction of ammonia detoxification during liver damage and regeneration
    • Schliess, F. et al. Integrated metabolic spatial-temporal model for the prediction of ammonia detoxification during liver damage and regeneration. Hepatology 60, 2040-2051 (2014).
    • (2014) Hepatology , vol.60 , pp. 2040-2051
    • Schliess, F.1
  • 6
    • 84907915031 scopus 로고    scopus 로고
    • Multiscale digital Arabidopsis predicts individual organ and whole-organism growth
    • Chew, Y. H. et al. Multiscale digital Arabidopsis predicts individual organ and whole-organism growth. Proc. Natl Acad. Sci. 111, E4127-E4136 (2014).
    • (2014) Proc. Natl Acad. Sci. , vol.111 , pp. E4127-E4136
    • Chew, Y.H.1
  • 7
    • 84865739425 scopus 로고    scopus 로고
    • Architecture of the human regulatory network derived from ENCODE data
    • Gerstein, M. B. et al. Architecture of the human regulatory network derived from ENCODE data. Nature 489, 91-100 (2012).
    • (2012) Nature , vol.489 , pp. 91-100
    • Gerstein, M.B.1
  • 8
    • 84866361701 scopus 로고    scopus 로고
    • Circuitry and dynamics of human transcription factor regulatory networks
    • Neph, S. et al. Circuitry and dynamics of human transcription factor regulatory networks. Cell 150, 1274-1286 (2012).
    • (2012) Cell , vol.150 , pp. 1274-1286
    • Neph, S.1
  • 9
    • 0036207347 scopus 로고    scopus 로고
    • And simulation of genetic regulatory systems: A literature review
    • De Jong, H. Modeling and simulation of genetic regulatory systems: a literature review. J. Comput. Biol. 9, 67-103 (2002).
    • (2002) J. Comput. Biol. , vol.9 , pp. 67-103
    • De Jong, H.1    Modeling2
  • 11
    • 0014733809 scopus 로고
    • Biochemical systems analysis. Dynamic solutions using a power-law approximation
    • Savageau, M. A. Biochemical systems analysis. Dynamic solutions using a power-law approximation. J. Theor. Biol. 26, 215-226 (1970).
    • (1970) J. Theor. Biol. , vol.26 , pp. 215-226
    • Savageau, M.A.1
  • 13
    • 0024842144 scopus 로고
    • Metabolic dynamics in the human red cell: Part I - A comprehensive kinetic model
    • Joshi, A. & Palsson, B. O. Metabolic dynamics in the human red cell: Part I- A comprehensive kinetic model. J. Theor. Biol. 141, 515-528 (1989).
    • (1989) J. Theor. Biol. , vol.141 , pp. 515-528
    • Joshi, A.1    Palsson, B.O.2
  • 14
    • 0001424903 scopus 로고
    • An amplified sensitivity arising from covalent modification in biological systems
    • Goldbeter, A. & Koshland, D. An amplified sensitivity arising from covalent modification in biological systems. Proc. Natl Acad. Sci. USA 78, 6840-6844 (1981).
    • (1981) Proc. Natl Acad. Sci. USA , vol.78 , pp. 6840-6844
    • Goldbeter, A.1    Koshland, D.2
  • 15
    • 0031879114 scopus 로고    scopus 로고
    • Stochastic kinetic analysis of developmental pathway bifurcation in phage-infected Escherichia coli cells
    • Arkin, A., Ross, J. & Mcadams, H. H. Stochastic kinetic analysis of developmental pathway bifurcation in phage-infected Escherichia coli cells. Genetics 149, 1633-1648 (1998).
    • (1998) Genetics , vol.149 , pp. 1633-1648
    • Arkin, A.1    Ross, J.2    McAdams, H.H.3
  • 16
    • 0034644270 scopus 로고    scopus 로고
    • The segment polarity network is a robust developmental module
    • Von Dassow, G., Meir, E., Munro, E. & Odell, G. The segment polarity network is a robust developmental module. Nature 406, 188-192 (2000).
    • (2000) Nature , vol.406 , pp. 188-192
    • Von Dassow, G.1    Meir, E.2    Munro, E.3    Odell, G.4
  • 17
    • 0034688173 scopus 로고    scopus 로고
    • A synthetic oscillatory network of transcriptional regulators
    • Elowitz, M. B. & Leibler, S. A synthetic oscillatory network of transcriptional regulators. Nature 403, 335-338 (2000).
    • (2000) Nature , vol.403 , pp. 335-338
    • Elowitz, M.B.1    Leibler, S.2
  • 18
    • 0034688174 scopus 로고    scopus 로고
    • Construction of a genetic toggle switch in Escherichia coli
    • Gardner, T., Cantor, C. & Collins, J. Construction of a genetic toggle switch in Escherichia coli. Nature 403, 339-342 (2000).
    • (2000) Nature , vol.403 , pp. 339-342
    • Gardner, T.1    Cantor, C.2    Collins, J.3
  • 19
    • 0014489272 scopus 로고
    • Metabolic stability and epigenesis in randomly constructed genetic nets
    • Kauffman, S. A. Metabolic stability and epigenesis in randomly constructed genetic nets. J. Theor. Biol. 22, 437-467 (1969).
    • (1969) J. Theor. Biol. , vol.22 , pp. 437-467
    • Kauffman, S.A.1
  • 20
    • 0015823097 scopus 로고
    • Boolean formalization of genetic control circuits
    • Thomas, R. Boolean formalization of genetic control circuits. J. Theor. Biol. 42, 563-585 (1973).
    • (1973) J. Theor. Biol. , vol.42 , pp. 563-585
    • Thomas, R.1
  • 21
    • 0742305866 scopus 로고    scopus 로고
    • Network biology: Understanding the cell's functional organization
    • Barabási, A.-L. & Oltvai, Z. N. Network biology: understanding the cell's functional organization. Nature Rev. Genet. 5, 101-113 (2004).
    • (2004) Nature Rev. Genet. , vol.5 , pp. 101-113
    • Barabási, A.-L.1    Oltvai, Z.N.2
  • 22
    • 84892788440 scopus 로고    scopus 로고
    • Constraint-based models predict metabolic and associated cellular functions
    • Bordbar, A., Monk, J. M., King, Z. A. & Palsson, B. O. Constraint-based models predict metabolic and associated cellular functions. Nature Rev. Genet. 15, 107-120 (2014).
    • (2014) Nature Rev. Genet. , vol.15 , pp. 107-120
    • Bordbar, A.1    Monk, J.M.2    King, Z.A.3    Palsson, B.O.4
  • 23
    • 14844321288 scopus 로고    scopus 로고
    • Space in systems biology of signaling pathways-towards intracellular molecular crowding in silico
    • Takahashi, K., Arjunan, S. N. V. & Tomita, M. Space in systems biology of signaling pathways-towards intracellular molecular crowding in silico. FEBS Lett. 579, 1783-1788 (2005).
    • (2005) FEBS Lett. , vol.579 , pp. 1783-1788
    • Takahashi, K.1    Arjunan, S.N.V.2    Tomita, M.3
  • 24
    • 34548141875 scopus 로고    scopus 로고
    • Computational methods for diffusion-influenced biochemical reactions
    • Dobrzynski, M., Rodríguez, J. V., Kaandorp, J. A. & Blom, J. G. Computational methods for diffusion-influenced biochemical reactions. Bioinformatics 23, 1969-1977 (2007).
    • (2007) Bioinformatics , vol.23 , pp. 1969-1977
    • Dobrzynski, M.1    Rodríguez, J.V.2    Kaandorp, J.A.3    Blom, J.G.4
  • 25
    • 75649111192 scopus 로고    scopus 로고
    • The genetic landscape of a cell
    • Costanzo, M. et al. The genetic landscape of a cell. Science 327, 425-431 (2010).
    • (2010) Science , vol.327 , pp. 425-431
    • Costanzo, M.1
  • 26
    • 27144530248 scopus 로고    scopus 로고
    • Towards a proteome-scale map of the human protein-protein interaction network
    • Rual, J.-F. et al. Towards a proteome-scale map of the human protein-protein interaction network. Nature 437, 1173-1178 (2005).
    • (2005) Nature , vol.437 , pp. 1173-1178
    • Rual, J.-F.1
  • 27
    • 25144498379 scopus 로고    scopus 로고
    • A human protein-protein interaction network: A resource for annotating the proteome
    • Stelzl, U. et al. A human protein-protein interaction network: a resource for annotating the proteome. Cell 122, 957-968 (2005).
    • (2005) Cell , vol.122 , pp. 957-968
    • Stelzl, U.1
  • 28
    • 84894876824 scopus 로고    scopus 로고
    • A competitive protein interaction network buffers Oct4-mediated differentiation to promote pluripotency in embryonic stem cells
    • Munõz Descalzo, S. et al. A competitive protein interaction network buffers Oct4-mediated differentiation to promote pluripotency in embryonic stem cells. Mol. Syst. Biol. 9, 694 (2013).
    • (2013) Mol. Syst. Biol. , vol.9 , pp. 694
    • Munõz Descalzo, S.1
  • 29
    • 84923692243 scopus 로고    scopus 로고
    • Construction and validation of a regulatory network for pluripotency and self-renewal of mouse embryonic stem cells
    • Xu, H., Ang, Y.-S., Sevilla, A., Lemischka I. R. & Ma'ayan, A. Construction and validation of a regulatory network for pluripotency and self-renewal of mouse embryonic stem cells. PLoS Comput. Biol. 10, e1003777 (2014).
    • (2014) PLoS Comput. Biol. , vol.10 , pp. e1003777
    • Xu, H.1    Ang, Y.-S.2    Sevilla, A.3    Lemischka, I.R.4    Ma'Ayan, A.5
  • 30
    • 65649116572 scopus 로고    scopus 로고
    • Human induced pluripotent stem cells free of vector and transgene sequences
    • Yu, J. et al. Human induced pluripotent stem cells free of vector and transgene sequences. Science 324, 797-801 (2009).
    • (2009) Science , vol.324 , pp. 797-801
    • Yu, J.1
  • 31
    • 40749104852 scopus 로고    scopus 로고
    • An extended transcriptional network for pluripotency of embryonic stem cells
    • Kim, J., Chu, J., Shen, X., Wang, J. & Orkin, S. H. An extended transcriptional network for pluripotency of embryonic stem cells. Cell 132, 1049-1061 (2008).
    • (2008) Cell , vol.132 , pp. 1049-1061
    • Kim, J.1    Chu, J.2    Shen, X.3    Wang, J.4    Orkin, S.H.5
  • 32
    • 25144525014 scopus 로고    scopus 로고
    • Core transcriptional regulatory circuitry in human embryonic stem cells
    • Boyer, L. A. et al. Core transcriptional regulatory circuitry in human embryonic stem cells. Cell 122, 947-956 (2005).
    • (2005) Cell , vol.122 , pp. 947-956
    • Boyer, L.A.1
  • 33
    • 42649091463 scopus 로고    scopus 로고
    • Characterization of the proneural gene regulatory network during mouse telencephalon development
    • Gohlke, J. M. et al. Characterization of the proneural gene regulatory network during mouse telencephalon development. BMC Biol. 6, 15 (2008).
    • (2008) BMC Biol. , vol.6 , pp. 15
    • Gohlke, J.M.1
  • 34
    • 84859215167 scopus 로고    scopus 로고
    • Serotonergic transcriptional networks and potential importance to mental health
    • Deneris, E. S. & Wyler, S. C. Serotonergic transcriptional networks and potential importance to mental health. Nature Neurosci. 15, 519-527 (2012).
    • (2012) Nature Neurosci. , vol.15 , pp. 519-527
    • Deneris, E.S.1    Wyler, S.C.2
  • 37
    • 84858983547 scopus 로고    scopus 로고
    • KEGG for integration and interpretation of large-scale molecular data sets
    • Kanehisa, M., Goto, S., Sato, Y., Furumichi, M. & Tanabe, M. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res. 40, D109-D114 (2012).
    • (2012) Nucleic Acids Res. , vol.40 , pp. D109-D114
    • Kanehisa, M.1    Goto, S.2    Sato, Y.3    Furumichi, M.4    Tanabe, M.5
  • 38
    • 84891753483 scopus 로고    scopus 로고
    • The Reactome pathway knowledgebase
    • Croft, D. et al. The Reactome pathway knowledgebase. Nucleic Acids Res. 42, D472-D477 (2014).
    • (2014) Nucleic Acids Res. , vol.42 , pp. D472-D477
    • Croft, D.1
  • 39
    • 0032568043 scopus 로고    scopus 로고
    • Functional capabilities of molecular network components controlling the mammalian G1/S cell cycle phase transition
    • Kohn, K. Functional capabilities of molecular network components controlling the mammalian G1/S cell cycle phase transition. Oncogene 16, 1065-1075 (1998).
    • (1998) Oncogene , vol.16 , pp. 1065-1075
    • Kohn, K.1
  • 40
    • 68449103579 scopus 로고    scopus 로고
    • The systems biology graphical notation
    • Le Novère, N. et al. The Systems Biology Graphical Notation. Nature Biotech. 27, 735-741 (2009).
    • (2009) Nature Biotech. , vol.27 , pp. 735-741
    • Le Novère, N.1
  • 41
    • 50849139490 scopus 로고    scopus 로고
    • Cataloging and organizing p73 interactions in cell cycle arrest and apoptosis
    • Tozluoglu, M., Karaca, E., Haliloglu, T. & Nussinov, R. Cataloging and organizing p73 interactions in cell cycle arrest and apoptosis. Nucleic Acids Res. 36, 5033-5049 (2008).
    • (2008) Nucleic Acids Res. , vol.36 , pp. 5033-5049
    • Tozluoglu, M.1    Karaca, E.2    Haliloglu, T.3    Nussinov, R.4
  • 42
    • 0032776303 scopus 로고    scopus 로고
    • Molecular interaction map of the mammalian cell cycle control and DNA repair systems
    • Kohn, K. Molecular interaction map of the mammalian cell cycle control and DNA repair systems. Mol. Biol. Cell 10, 2703-2734 (1999).
    • (1999) Mol. Biol. Cell , vol.10 , pp. 2703-2734
    • Kohn, K.1
  • 43
    • 2442464889 scopus 로고    scopus 로고
    • Apoptosis defects and chemotherapy resistance: Molecular interaction maps and networks
    • Pommier, Y., Sordet, O., Antony, S., Hayward, R. L. & Kohn, K. W. Apoptosis defects and chemotherapy resistance: molecular interaction maps and networks. Oncogene 23, 2934-2949 (2004).
    • (2004) Oncogene , vol.23 , pp. 2934-2949
    • Pommier, Y.1    Sordet, O.2    Antony, S.3    Hayward, R.L.4    Kohn, K.W.5
  • 44
    • 33747366698 scopus 로고    scopus 로고
    • Rules for modeling signal-transduction systems
    • Hlavacek, W. S. et al. Rules for modeling signal-transduction systems. Sci. STKE 2006, re6 (2006).
    • (2006) Sci. STKE , vol.2006 , pp. re6
    • Hlavacek, W.S.1
  • 47
    • 84868089503 scopus 로고    scopus 로고
    • Modeling of tumor progression in NSCLC and intrinsic resistance to TKI in loss of PTEN expression
    • Bidkhori, G., Moeini, A. & Masoudi-Nejad, A. Modeling of tumor progression in NSCLC and intrinsic resistance to TKI in loss of PTEN expression. PLoS ONE 7, e48004 (2012).
    • (2012) PLoS ONE , vol.7 , pp. e48004
    • Bidkhori, G.1    Moeini, A.2    Masoudi-Nejad, A.3
  • 48
    • 33746021158 scopus 로고    scopus 로고
    • Scaffolding protein Grb2-associated binder 1 sustains epidermal growth factor-induced mitogenic and survival signaling by multiple positive feedback loops
    • Kiyatkin, A. et al. Scaffolding protein Grb2-associated binder 1 sustains epidermal growth factor-induced mitogenic and survival signaling by multiple positive feedback loops. J. Biol. Chem. 281, 19925-19938 (2006).
    • (2006) J. Biol. Chem. , vol.281 , pp. 19925-19938
    • Kiyatkin, A.1
  • 49
    • 46549089054 scopus 로고    scopus 로고
    • Simulation of the regulation of EGFR endocytosis and EGFR-ERK signaling by endophilin-mediated RhoA-EGFR crosstalk
    • Ung, C. Y. et al. Simulation of the regulation of EGFR endocytosis and EGFR-ERK signaling by endophilin-mediated RhoA-EGFR crosstalk. FEBS Lett. 582, 2283-2290 (2008).
    • (2008) FEBS Lett. , vol.582 , pp. 2283-2290
    • Ung, C.Y.1
  • 50
    • 0037448456 scopus 로고    scopus 로고
    • Control mechanism of JAK/STAT signal transduction pathway
    • Yamada, S., Shiono, S., Joo, A. & Yoshimura, A. Control mechanism of JAK/STAT signal transduction pathway. FEBS Lett. 534, 190-196 (2003).
    • (2003) FEBS Lett. , vol.534 , pp. 190-196
    • Yamada, S.1    Shiono, S.2    Joo, A.3    Yoshimura, A.4
  • 51
    • 0037342537 scopus 로고    scopus 로고
    • The systems biology markup language (SBML): A medium for representation and exchange of biochemical network models
    • Hucka, M. et al. The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19, 524-531 (2003).
    • (2003) Bioinformatics , vol.19 , pp. 524-531
    • Hucka, M.1
  • 52
    • 84891789990 scopus 로고    scopus 로고
    • The 2014 Nucleic Acids Research Database Issue and an updated NAR online Molecular Biology Database Collection
    • Fernández-Suárez, X. M., Rigden, D. J. & Galperin, M. Y. The 2014 Nucleic Acids Research Database Issue and an updated NAR online Molecular Biology Database Collection. Nucleic Acids Res. 42, D1-D6 (2014).
    • (2014) Nucleic Acids Res. , vol.42 , pp. D1-D6
    • Fernández-Suárez, X.M.1    Rigden, D.J.2    Galperin, M.Y.3
  • 53
    • 84891799734 scopus 로고    scopus 로고
    • The MIntAct project-IntAct as a common curation platform for 11 molecular interaction databases
    • Orchard, S. et al. The MIntAct project-IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res. 42, D358-D363 (2014).
    • (2014) Nucleic Acids Res. , vol.42 , pp. D358-D363
    • Orchard, S.1
  • 54
    • 84876515907 scopus 로고    scopus 로고
    • STRING v9.1: Protein-protein interaction networks, with increased coverage and integration
    • Franceschini, A. et al. STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res. 41, D808-D815 (2013).
    • (2013) Nucleic Acids Res. , vol.41 , pp. D808-D815
    • Franceschini, A.1
  • 55
    • 84891774001 scopus 로고    scopus 로고
    • The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases
    • Caspi, R. et al. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases. Nucleic Acids Res. 42, D459-D471 (2014).
    • (2014) Nucleic Acids Res. , vol.42 , pp. D459-D471
    • Caspi, R.1
  • 56
    • 84876008750 scopus 로고    scopus 로고
    • The ConsensusPathDB interaction database: 2013 update
    • Kamburov, A., Stelzl, U., Lehrach, H. & Herwig, R. The ConsensusPathDB interaction database: 2013 update. Nucleic Acids Res. 41, D793-D800 (2013).
    • (2013) Nucleic Acids Res. , vol.41 , pp. D793-D800
    • Kamburov, A.1    Stelzl, U.2    Lehrach, H.3    Herwig, R.4
  • 57
  • 58
    • 84862214722 scopus 로고    scopus 로고
    • SABIO-RK-database for biochemical reaction kinetics
    • Wittig, U. et al. SABIO-RK-database for biochemical reaction kinetics. Nucleic Acids Res. 40, D790-D796 (2012).
    • (2012) Nucleic Acids Res. , vol.40 , pp. D790-D796
    • Wittig, U.1
  • 59
    • 78651330012 scopus 로고    scopus 로고
    • BRENDA, the enzyme information system in 2011
    • Scheer, M. et al. BRENDA, the enzyme information system in 2011. Nucleic Acids Res. 39, D670-D676 (2011).
    • (2011) Nucleic Acids Res. , vol.39 , pp. D670-D676
    • Scheer, M.1
  • 60
    • 84886740491 scopus 로고    scopus 로고
    • Path2Models: Large-scale generation of computational models from biochemical pathway maps
    • Büchel, F. et al. Path2Models: large-scale generation of computational models from biochemical pathway maps. BMC Syst. Biol. 7, 116 (2013).
    • (2013) BMC Syst. Biol. , vol.7 , pp. 116
    • Büchel, F.1
  • 62
    • 84859371992 scopus 로고    scopus 로고
    • Gene network inference and visualization tools for biologists: Application to new human transcriptome datasets
    • Hurley, D. et al. Gene network inference and visualization tools for biologists: application to new human transcriptome datasets. Nucleic Acids Res. 40, 2377-2398 (2012).
    • (2012) Nucleic Acids Res. , vol.40 , pp. 2377-2398
    • Hurley, D.1
  • 63
    • 84897655065 scopus 로고    scopus 로고
    • High-throughput sequencing reveals the disruption of methylation of imprinted gene in induced pluripotent stem cells
    • Chang, G. et al. High-throughput sequencing reveals the disruption of methylation of imprinted gene in induced pluripotent stem cells. Cell Res. 24, 293-306 (2014).
    • (2014) Cell Res. , vol.24 , pp. 293-306
    • Chang, G.1
  • 64
    • 84891892050 scopus 로고    scopus 로고
    • Reverse engineering and identification in systems biology: Strategies, perspectives and challenges
    • Villaverde, A. F. & Banga, J. R. Reverse engineering and identification in systems biology: strategies, perspectives and challenges. J. R. Soc. Interface. 11, 20130505 (2013).
    • (2013) J. R. Soc. Interface. , vol.11 , pp. 20130505
    • Villaverde, A.F.1    Banga, J.R.2
  • 65
    • 77957110013 scopus 로고    scopus 로고
    • Advantages and limitations of current network inference methods
    • De Smet, R. & Marchal, K. Advantages and limitations of current network inference methods. Nature Rev. Microbiol. 8, 717-729 (2010).
    • (2010) Nature Rev. Microbiol. , vol.8 , pp. 717-729
    • De Smet, R.1    Marchal, K.2
  • 66
    • 70449529712 scopus 로고    scopus 로고
    • Reverse engineering and verification of gene networks: Principles, assumptions, and limitations of present methods and future perspectives
    • He, F., Balling, R. & Zeng, A.-P. Reverse engineering and verification of gene networks: principles, assumptions, and limitations of present methods and future perspectives. J. Biotechnol. 144, 190-203 (2009).
    • (2009) J. Biotechnol. , vol.144 , pp. 190-203
    • He, F.1    Balling, R.2    Zeng, A.-P.3
  • 67
    • 84869882656 scopus 로고    scopus 로고
    • TIGRESS: Trustful Inference of Gene REgulation using Stability Selection
    • Haury, A., Mordelet, F., Vera-licona, P. & Vert, J. TIGRESS: Trustful Inference of Gene REgulation using Stability Selection. BMC Syst. Biol. 6, 145 (2012).
    • (2012) BMC Syst. Biol. , vol.6 , pp. 145
    • Haury, A.1    Mordelet, F.2    Vera-Licona, P.3    Vert, J.4
  • 68
    • 84901837819 scopus 로고    scopus 로고
    • Defining an essential transcription factor program for naive pluripotency
    • Dunn, S.-J. Martello, G., Yordanov, B., Emmott, S. & Smith, T. G. Defining an essential transcription factor program for naive pluripotency. Science. 344, 1156-1160 (2014).
    • (2014) Science , vol.344 , pp. 1156-1160
    • Dunn Martello -J S, G.1    Yordanov, B.2    Emmott, S.3    Smith, T.G.4
  • 69
    • 33846400424 scopus 로고    scopus 로고
    • Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles
    • Faith, J. J. et al. Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biol. 5, e8 (2007).
    • (2007) PLoS Biol. , vol.5 , pp. e8
    • Faith, J.J.1
  • 70
    • 33947305781 scopus 로고    scopus 로고
    • ARACNE: An algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context
    • Margolin, A. A. et al. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinform. 7 (Suppl. 1), 7 (2006).
    • (2006) BMC Bioinform. , vol.7 , pp. 7
    • Margolin, A.A.1
  • 72
  • 73
    • 12344259602 scopus 로고    scopus 로고
    • Advances to Bayesian network inference for generating causal networks from observational biological data
    • Yu, J., Smith, V. A., Wang, P. P., Hartemink, A. J. & Jarvis, E. D. Advances to Bayesian network inference for generating causal networks from observational biological data. Bioinformatics 20, 3594-3603 (2004).
    • (2004) Bioinformatics , vol.20 , pp. 3594-3603
    • Yu, J.1    Smith, V.A.2    Wang, P.P.3    Hartemink, A.J.4    Jarvis, E.D.5
  • 74
    • 17644427718 scopus 로고    scopus 로고
    • Causal protein-signaling networks derived from multiparameter single-cell data
    • Sachs, K., Perez, O., Pe'er, D., Lauffenburger, D. A. & Nolan, G. P. Causal protein-signaling networks derived from multiparameter single-cell data. Science 308, 523-529 (2005).
    • (2005) Science , vol.308 , pp. 523-529
    • Sachs, K.1    Perez, O.2    Pe'Er, D.3    Lauffenburger, D.A.4    Nolan, G.P.5
  • 75
    • 84883771767 scopus 로고    scopus 로고
    • Network deconvolution as a general method to distinguish direct dependencies in networks
    • Feizi, S., Marbach, D., Médard, M. & Kellis, M. Network deconvolution as a general method to distinguish direct dependencies in networks. Nature Biotech. 31, 726-733 (2013).
    • (2013) Nature Biotech. , vol.31 , pp. 726-733
    • Feizi, S.1    Marbach, D.2    Médard, M.3    Kellis, M.4
  • 76
    • 51049117937 scopus 로고    scopus 로고
    • Models from experiments: Combinatorial drug perturbations of cancer cells
    • Nelander, S. et al. Models from experiments: combinatorial drug perturbations of cancer cells. Mol. Syst. Biol. 4, 216 (2008).
    • (2008) Mol. Syst. Biol. , vol.4 , pp. 216
    • Nelander, S.1
  • 77
    • 33747813561 scopus 로고    scopus 로고
    • The Inferelator: An algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo
    • Bonneau, R. et al. The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo. Genome Biol. 7, R36 (2006).
    • (2006) Genome Biol. , vol.7 , pp. R36
    • Bonneau, R.1
  • 78
    • 0038048325 scopus 로고    scopus 로고
    • Inferring genetic networks and identifying compound mode of action via expression profiling
    • Gardner, T. S., di Bernardo, D., Lorenz, D. & Collins, J. J. Inferring genetic networks and identifying compound mode of action via expression profiling. Science 301, 102-105 (2003).
    • (2003) Science , vol.301 , pp. 102-105
    • Gardner, T.S.1    Di Bernardo, D.2    Lorenz, D.3    Collins, J.J.4
  • 79
    • 84923642420 scopus 로고    scopus 로고
    • Dynamic control of positional information in the early
    • Jaeger, J. et al. Dynamic control of positional information in the early Drosophila embryo. 430, 2-5 (2004).
    • (2004) Drosophila Embryo , vol.430 , pp. 2-5
    • Jaeger, J.1
  • 80
    • 63049128934 scopus 로고    scopus 로고
    • A yeast synthetic network for in vivo assessment of reverse-engineering and modeling approaches
    • Cantone, I. et al. A yeast synthetic network for in vivo assessment of reverse-engineering and modeling approaches. Cell 137, 172-181 (2009).
    • (2009) Cell , vol.137 , pp. 172-181
    • Cantone, I.1
  • 81
    • 84870305264 scopus 로고    scopus 로고
    • Wisdom of crowds for robust gene network inference
    • Marbach, D. et al. Wisdom of crowds for robust gene network inference. Nature Methods 9, 796-804 (2012).
    • (2012) Nature Methods , vol.9 , pp. 796-804
    • Marbach, D.1
  • 82
    • 84923647642 scopus 로고    scopus 로고
    • NAIL, a software toolset for inferring, analyzing and visualizing regulatory networks
    • Hurley, D. G. et al. NAIL, a software toolset for inferring, analyzing and visualizing regulatory networks. Bioinformatics 31, 277-278 (2015).
    • (2015) Bioinformatics , vol.31 , pp. 277-278
    • Hurley, D.G.1
  • 84
    • 84883217605 scopus 로고    scopus 로고
    • Using chemical kinetics to model biochemical pathways
    • Le Novère, N. & Endler, L. Using chemical kinetics to model biochemical pathways. Methods Mol. Biol. 1021, 147-67 (2013).
    • (2013) Methods Mol. Biol. , vol.1021 , pp. 147-167
    • Le Novère, N.1    Endler, L.2
  • 85
    • 84879801381 scopus 로고    scopus 로고
    • The systems biology simulation core algorithm
    • Keller, R. et al. The systems biology simulation core algorithm. BMC Syst. Biol. 7, 55 (2013).
    • (2013) BMC Syst. Biol. , vol.7 , pp. 55
    • Keller, R.1
  • 86
    • 33845368513 scopus 로고    scopus 로고
    • COPASI- A COmplex PAthway SImulator
    • Hoops, S. et al. COPASI- A COmplex PAthway SImulator. Bioinformatics 22, 3067-3074 (2006).
    • (2006) Bioinformatics , vol.22 , pp. 3067-3074
    • Hoops, S.1
  • 87
    • 70350569876 scopus 로고    scopus 로고
    • Comparing different ODE modelling approaches for gene regulatory networks
    • Polynikis, A., Hogan, S. J. & Bernardo, M. Comparing different ODE modelling approaches for gene regulatory networks. J. Theor. Biol. 261, 511-530 (2009).
    • (2009) J. Theor. Biol. , vol.261 , pp. 511-530
    • Polynikis, A.1    Hogan, S.J.2    Bernardo, M.3
  • 88
    • 84859088981 scopus 로고    scopus 로고
    • A dynamic network model of mTOR signaling reveals TSC-independent mTORC2 regulation
    • Dalle Pezze, P. et al. A dynamic network model of mTOR signaling reveals TSC-independent mTORC2 regulation. Sci. Signal. 5, ra25 (2012).
    • (2012) Sci. Signal. , vol.5 , pp. ra25
    • Dalle Pezze, P.1
  • 89
    • 7444254365 scopus 로고    scopus 로고
    • Oscillations in NF-B signaling control the dynamics of gene expression
    • Nelson, D. et al. Oscillations in NF-B signaling control the dynamics of gene expression. Science 306, 704-708 (2004).
    • (2004) Science , vol.306 , pp. 704-708
    • Nelson, D.1
  • 90
    • 64849104716 scopus 로고    scopus 로고
    • Pulsatile stimulation determines timing and specificity of NF-B-dependent transcription
    • Ashall, L. et al. Pulsatile stimulation determines timing and specificity of NF-B-dependent transcription. Science 324, 242-246 (2009).
    • (2009) Science , vol.324 , pp. 242-246
    • Ashall, L.1
  • 92
    • 0029790351 scopus 로고    scopus 로고
    • Ultrasensitivity in the mitogen-activated protein kinase cascade
    • Huang, C. Y. & Ferrell, J. E. Ultrasensitivity in the mitogen-activated protein kinase cascade. Proc. Natl Acad. Sci. USA 93, 10078-10083 (1996).
    • (1996) Proc. Natl Acad. Sci. USA , vol.93 , pp. 10078-10083
    • Huang, C.Y.1    Ferrell, J.E.2
  • 93
    • 77956289955 scopus 로고    scopus 로고
    • Classic and contemporary approaches to modeling biochemical reactions
    • Chen, W. W., Niepel, M. & Sorger, P. K. Classic and contemporary approaches to modeling biochemical reactions. Genes Dev. 861-1875 (2010).
    • (2010) Genes Dev. , pp. 861-1875
    • Chen, W.W.1    Niepel, M.2    Sorger, P.K.3
  • 96
    • 84883050022 scopus 로고    scopus 로고
    • Biochemical systems theory: A review
    • Voit, E. O. Biochemical systems theory: a review. ISRN Biomath. 2013, 1-53 (2013).
    • (2013) ISRN Biomath , vol.2013 , pp. 1-53
    • Voit, E.O.1
  • 97
    • 34548621871 scopus 로고    scopus 로고
    • Dynamics of a three-variable nonlinear model of vasomotion: Comparison of theory and experiment
    • Parthimos, D., Haddock, R. E., Hill, C. E. & Griffith, T. M. Dynamics of a three-variable nonlinear model of vasomotion: comparison of theory and experiment. Biophys. J. 93, 1534-1556 (2007).
    • (2007) Biophys. J. , vol.93 , pp. 1534-1556
    • Parthimos, D.1    Haddock, R.E.2    Hill, C.E.3    Griffith, T.M.4
  • 98
    • 79955553550 scopus 로고    scopus 로고
    • Origin of bistability underlying mammalian cell cycle entry
    • Yao, G., Tan, C., West, M., Nevins, J. R. & You, L. Origin of bistability underlying mammalian cell cycle entry. Mol. Syst. Biol. 7, 485 (2011).
    • (2011) Mol. Syst. Biol. , vol.7 , pp. 485
    • Yao, G.1    Tan, C.2    West, M.3    Nevins, J.R.4    You, L.5
  • 99
    • 56749160113 scopus 로고    scopus 로고
    • Design principles of biochemical oscillators
    • Novák, B. & Tyson, J. J. Design principles of biochemical oscillators. Nature Rev. Mol. Cell Biol. 9, 981-991 (2008).
    • (2008) Nature Rev. Mol. Cell Biol. , vol.9 , pp. 981-991
    • Novák, B.1    Tyson, J.J.2
  • 100
    • 42449157505 scopus 로고    scopus 로고
    • Modeling the segmentation clock as a network of coupled oscillations in the Notch, Wnt and FGF signaling pathways
    • Goldbeter, A. & Pourquié, O. Modeling the segmentation clock as a network of coupled oscillations in the Notch, Wnt and FGF signaling pathways. J. Theor. Biol. 252, 574-585 (2008).
    • (2008) J. Theor. Biol. , vol.252 , pp. 574-585
    • Goldbeter, A.1    Pourquié, O.2
  • 101
    • 40149093742 scopus 로고    scopus 로고
    • Notch signalling synchronizes the zebrafish segmentation clock but is not needed to create somite boundaries
    • Ozbudak, E. M. & Lewis, J. Notch signalling synchronizes the zebrafish segmentation clock but is not needed to create somite boundaries. PLoS Genet. 4, e15 (2008).
    • (2008) PLoS Genet. , vol.4 , pp. e15
    • Ozbudak, E.M.1    Lewis, J.2
  • 102
    • 0015609281 scopus 로고
    • The logical analysis of continuous, non-linear biochemical control networks
    • Glass, L. & Kauffman, S. The logical analysis of continuous, non-linear biochemical control networks. J. Theor. Biol. 39, 103-129 (1973).
    • (1973) J. Theor. Biol. , vol.39 , pp. 103-129
    • Glass, L.1    Kauffman, S.2
  • 103
    • 33645053513 scopus 로고    scopus 로고
    • Discrete time piecewise affine models of genetic regulatory networks
    • Coutinho, R., Fernandez, B., Lima, R. & Meyroneinc, A. Discrete time piecewise affine models of genetic regulatory networks. J. Math. 52, 524-570 (2006).
    • (2006) J. Math. , vol.52 , pp. 524-570
    • Coutinho, R.1    Fernandez, B.2    Lima, R.3    Meyroneinc, A.4
  • 104
    • 1242333310 scopus 로고    scopus 로고
    • Qualitative simulation of genetic regulatory networks using piecewise-linear models
    • De Jong, H. et al. Qualitative simulation of genetic regulatory networks using piecewise-linear models. Bull. Math. Biol. 66, 301-340 (2004).
    • (2004) Bull. Math. Biol. , vol.66 , pp. 301-340
    • De Jong, H.1
  • 105
    • 0345269975 scopus 로고    scopus 로고
    • Genetic Network Analyzer: Qualitative simulation of genetic regulatory networks
    • De Jong, H., Geiselmann, J., Hernandez, C. & Page, M. Genetic Network Analyzer: qualitative simulation of genetic regulatory networks. Bioinformatics 19, 336-344 (2003).
    • (2003) Bioinformatics , vol.19 , pp. 336-344
    • De Jong, H.1    Geiselmann, J.2    Hernandez, C.3    Page, M.4
  • 106
    • 0242574982 scopus 로고    scopus 로고
    • Parameter estimation in biochemical pathways: A comparison of global optimization methods
    • Moles, C. G., Mendes, P. & Banga, J. R. Parameter estimation in biochemical pathways: a comparison of global optimization methods. Genome Res. 13, 2467-2474 (2003).
    • (2003) Genome Res. , vol.13 , pp. 2467-2474
    • Moles, C.G.1    Mendes, P.2    Banga, J.R.3
  • 108
    • 0031583031 scopus 로고    scopus 로고
    • Establishment of the dorso-ventral pattern during embryonic development of Drosophila melanogaster: A logical analysis
    • Sánchez, L., Van Helden, J. & Thieffry, D. Establishment of the dorso-ventral pattern during embryonic development of Drosophila melanogaster: a logical analysis. J. Theor. Biol. 189, 377-389 (1997).
    • (1997) J. Theor. Biol. , vol.189 , pp. 377-389
    • Sánchez, L.1    Van Helden, J.2    Thieffry, D.3
  • 109
    • 0032549745 scopus 로고    scopus 로고
    • Genomic cis-regulatory logic: Experimental and computational analysis of a sea urchin gene
    • Yuh, C.-H., Bolouri, H. & Davidson, E. H. Genomic cis-regulatory logic: experimental and computational analysis of a sea urchin gene. Science 279, 1896-1902 (1998).
    • (1998) Science , vol.279 , pp. 1896-1902
    • Yuh, C.-H.1    Bolouri, H.2    Davidson, E.H.3
  • 110
    • 84879923473 scopus 로고    scopus 로고
    • Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model
    • Bonzanni, N. et al. Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model. Bioinformatics 29, i80-i88 (2013).
    • (2013) Bioinformatics , vol.29 , pp. 180-188
    • Bonzanni, N.1
  • 111
    • 70449481350 scopus 로고    scopus 로고
    • Transforming Boolean models to continuous models: Methodology and application to T-cell receptor signaling
    • Wittmann, D. M. et al. Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling. BMC Syst. Biol. 3, 98 (2009).
    • (2009) BMC Syst. Biol. , vol.3 , pp. 98
    • Wittmann, D.M.1
  • 112
    • 77950825394 scopus 로고    scopus 로고
    • Mathematical modelling of cell-fate decision in response to death receptor engagement
    • Calzone, L. et al. Mathematical modelling of cell-fate decision in response to death receptor engagement. PLoS Comput. Biol. 6, e1000702 (2010).
    • (2010) PLoS Comput. Biol. , vol.6 , pp. e1000702
    • Calzone, L.1
  • 113
    • 84887303651 scopus 로고    scopus 로고
    • Integrative modelling of the influence of MAPK network on cancer cell fate decision
    • Grieco, L. et al. Integrative modelling of the influence of MAPK network on cancer cell fate decision. PLoS Comput. Biol. 9, e1003286 (2013).
    • (2013) PLoS Comput. Biol. , vol.9 , pp. e1003286
    • Grieco, L.1
  • 114
    • 50549088838 scopus 로고    scopus 로고
    • Synchronous versus asynchronous modeling of gene regulatory networks
    • Garg, A., Di Cara, A., Xenarios, I., Mendoza, L. & De Micheli, G. Synchronous versus asynchronous modeling of gene regulatory networks. Bioinformatics 24, 1917-1925 (2008).
    • (2008) Bioinformatics , vol.24 , pp. 1917-1925
    • Garg, A.1    Di Cara, A.2    Xenarios, I.3    Mendoza, L.4    De Micheli, G.5
  • 115
    • 36949019568 scopus 로고    scopus 로고
    • Hybrid modelling and dynamical analysis of gene regulatory networks with delays
    • Ahmad, J., Bernot, G., Comet, J.-P., Lime, D. & Roux, O. Hybrid modelling and dynamical analysis of gene regulatory networks with delays. Complexus 3, 231-251 (2006).
    • (2006) Complexus , vol.3 , pp. 231-251
    • Ahmad, J.1    Bernot, G.2    Comet, J.-P.3    Lime, D.4    Roux, O.5
  • 116
    • 0036184629 scopus 로고    scopus 로고
    • Probabilistic Boolean networks: A rule-based uncertainty model for gene regulatory networks
    • Shmulevich, I., Dougherty, E. R., Kim, S. & Zhang, W. Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks. Bioinformatics 18, 261-274 (2002).
    • (2002) Bioinformatics , vol.18 , pp. 261-274
    • Shmulevich, I.1    Dougherty, E.R.2    Kim, S.3    Zhang, W.4
  • 118
    • 84865318887 scopus 로고    scopus 로고
    • Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks
    • Liang, J. & Han, J. Stochastic Boolean networks: an efficient approach to modeling gene regulatory networks. BMC Syst. Biol. 6, 113 (2012).
    • (2012) BMC Syst. Biol. , vol.6 , pp. 113
    • Liang, J.1    Han, J.2
  • 121
    • 84867537553 scopus 로고    scopus 로고
    • CellNOptR: A flexible toolkit to train protein signaling networks to data using multiple logic formalisms
    • Terfve, C. et al. CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms. BMC Syst. Biol. 6, 133 (2012).
    • (2012) BMC Syst. Biol. , vol.6 , pp. 133
    • Terfve, C.1
  • 122
    • 84864952677 scopus 로고    scopus 로고
    • State-time spectrum of signal transduction logic models
    • MacNamara, A. & Terfve, C. State-time spectrum of signal transduction logic models. Phys. Biol. 9, 045003 (2012).
    • (2012) Phys. Biol. , vol.9 , pp. 045003
    • MacNamara, A.1    Terfve, C.2
  • 123
    • 84885676246 scopus 로고    scopus 로고
    • An overview of existing modeling tools making use of model checking in the analysis of biochemical networks
    • Carrillo, M. Góngora, P. A. & Rosenblueth, D. A. An overview of existing modeling tools making use of model checking in the analysis of biochemical networks. Front. Plant Sci. 3, 155 (2012).
    • (2012) Front. Plant Sci. , vol.3 , pp. 155
    • Carrillo Góngora M, P.A.1    Rosenblueth, D.A.2
  • 124
    • 84881616812 scopus 로고    scopus 로고
    • Moving from basic toward systems pharmacodynamic models
    • Jusko, W. J. Moving from basic toward systems pharmacodynamic models. J. Pharm. Sci. 102, 2930-2940 (2013).
    • (2013) J. Pharm. Sci. , vol.102 , pp. 2930-2940
    • Jusko, W.J.1
  • 125
    • 1542400036 scopus 로고    scopus 로고
    • A multi-algorithm, multi-timescale method for cell simulation
    • Takahashi, K., Kaizu, K., Hu, B. & Tomita, M. A multi-algorithm, multi-timescale method for cell simulation. Bioinformatics 20, 538-546 (2004).
    • (2004) Bioinformatics , vol.20 , pp. 538-546
    • Takahashi, K.1    Kaizu, K.2    Hu, B.3    Tomita, M.4
  • 126
    • 0029028963 scopus 로고
    • Circuit simulation of genetic networks
    • McAdams, H. & Shapiro, L. Circuit simulation of genetic networks. Science 269, 650-656 (1995).
    • (1995) Science , vol.269 , pp. 650-656
    • McAdams, H.1    Shapiro, L.2
  • 128
    • 84908190303 scopus 로고    scopus 로고
    • A model integration approach linking signalling and gene-regulatory logic with kinetic metabolic models
    • Ryll, A. et al. A model integration approach linking signalling and gene-regulatory logic with kinetic metabolic models. Biosystems 124, 26-38 (2014).
    • (2014) Biosystems , vol.124 , pp. 26-38
    • Ryll, A.1
  • 130
    • 33745178476 scopus 로고    scopus 로고
    • Integrated analysis of regulatory and metabolic networks reveals novel regulatory mechanisms in Saccharomyces cerevisiae
    • Herrgård, M. J., Lee, B., Portnoy, V. & Palsson, B. J. Integrated analysis of regulatory and metabolic networks reveals novel regulatory mechanisms in Saccharomyces cerevisiae. Genome Res. 16, 627-635 (2006).
    • (2006) Genome Res. , vol.16 , pp. 627-635
    • Herrgård, M.J.1    Lee, B.2    Portnoy, V.3    Palsson, B.J.4
  • 131
    • 34247183123 scopus 로고    scopus 로고
    • A genome-scale computational study of the interplay between transcriptional regulation and metabolism
    • Shlomi, T., Eisenberg, Y., Sharan, R. & Ruppin, E. A genome-scale computational study of the interplay between transcriptional regulation and metabolism. Mol. Syst. Biol. 3, 101 (2007).
    • (2007) Mol. Syst. Biol. , vol.3 , pp. 101
    • Shlomi, T.1    Eisenberg, Y.2    Sharan, R.3    Ruppin, E.4
  • 132
    • 84879748625 scopus 로고    scopus 로고
    • Integration of biochemical and electrical signaling-multiscale model of the medium spiny neuron of the striatum
    • Mattioni, M. & Le Novère, N. Integration of biochemical and electrical signaling-multiscale model of the medium spiny neuron of the striatum. PLoS ONE 8, e66811 (2013).
    • (2013) PLoS ONE , vol.8 , pp. e66811
    • Mattioni, M.1    Le Novère, N.2
  • 133
    • 84862295360 scopus 로고    scopus 로고
    • Guidelines for the use and interpretation of assays for monitoring autophagy
    • Klionsky, D. J. et al. Guidelines for the use and interpretation of assays for monitoring autophagy. Autophagy 8, 445-544 (2012).
    • (2012) Autophagy , vol.8 , pp. 445-544
    • Klionsky, D.J.1
  • 134
    • 0033555859 scopus 로고    scopus 로고
    • Emergent properties of networks of biological signaling pathways
    • Bhalla, U. & Iyengar, R. Emergent properties of networks of biological signaling pathways. Science 283, 381-387 (1999).
    • (1999) Science , vol.283 , pp. 381-387
    • Bhalla, U.1    Iyengar, R.2
  • 135
    • 49449096617 scopus 로고    scopus 로고
    • An allosteric model of calmodulin explains differential activation of PP2B and CaMKII
    • Stefan, M. I., Edelstein, S. J. & Le Novère, N. An allosteric model of calmodulin explains differential activation of PP2B and CaMKII. Proc. Natl Acad. Sci. USA 105, 10768-10773 (2008).
    • (2008) Proc. Natl Acad. Sci. USA , vol.105 , pp. 10768-10773
    • Stefan, M.I.1    Edelstein, S.J.2    Le Novère, N.3
  • 136
    • 28644433993 scopus 로고    scopus 로고
    • Minimum information requested in the annotation of biochemical models (MIRIAM)
    • Le Novère, N. et al. Minimum information requested in the annotation of biochemical models (MIRIAM). Nature Biotech. 23, 1509-1515 (2005).
    • (2005) Nature Biotech. , vol.23 , pp. 1509-1515
    • Le Novère, N.1
  • 137
    • 79955570036 scopus 로고    scopus 로고
    • Minimum information about a simulation experiment (MIASE)
    • Waltemath, D. et al. Minimum information about a simulation experiment (MIASE). PLoS Comput. Biol. 7, e1001122 (2011).
    • (2011) PLoS Comput. Biol. , vol.7 , pp. e1001122
    • Waltemath, D.1
  • 138
    • 83455162737 scopus 로고    scopus 로고
    • Reproducible computational biology experiments with SED-ML - The Simulation Experiment Description Markup Language
    • Waltemath, D. et al. Reproducible computational biology experiments with SED-ML-the Simulation Experiment Description Markup Language. BMC Syst. Biol. 5, 198 (2011).
    • (2011) BMC Syst. Biol. , vol.5 , pp. 198
    • Waltemath, D.1
  • 139
    • 28844464035 scopus 로고    scopus 로고
    • Core genetic module: The mixed feedback loop
    • François, P. & Hakim, V. Core genetic module: the mixed feedback loop. Phys. Rev. E 72, 031908 (2005).
    • (2005) Phys. Rev. e , vol.72 , pp. 031908
    • François, P.1    Hakim, V.2
  • 140
    • 67649771445 scopus 로고    scopus 로고
    • Logical modelling of regulatory networks with GINsim 2.3
    • Naldi, A. et al. Logical modelling of regulatory networks with GINsim 2.3. Biosystems 97, 134-139 (2009).
    • (2009) Biosystems , vol.97 , pp. 134-139
    • Naldi, A.1
  • 141
    • 33747877324 scopus 로고    scopus 로고
    • BIOCHAM: An environment for modeling biological systems and formalizing experimental knowledge
    • Calzone, L., Fages, F. & Soliman, S. BIOCHAM: an environment for modeling biological systems and formalizing experimental knowledge. Bioinformatics 22, 1805-1897 (2006).
    • (2006) Bioinformatics , vol.22 , pp. 1805-1897
    • Calzone, L.1    Fages, F.2    Soliman, S.3
  • 142
    • 9444266171 scopus 로고    scopus 로고
    • CellDesigner: A process diagram editor for gene-regulatory and biochemical networks
    • Funahashi, A., Morohashi, M., Kitano, H. & Tanimura, N. CellDesigner: a process diagram editor for gene-regulatory and biochemical networks. BIOSILICO 1, 159-162 (2003).
    • (2003) BIOSILICO , vol.1 , pp. 159-162
    • Funahashi, A.1    Morohashi, M.2    Kitano, H.3    Tanimura, N.4
  • 143
    • 70350669878 scopus 로고    scopus 로고
    • IBioSim: A tool for the analysis and design of genetic circuits
    • Myers, C. J. et al. iBioSim: a tool for the analysis and design of genetic circuits. Bioinformatics 25, 2848-2849 (2009).
    • (2009) Bioinformatics , vol.25 , pp. 2848-2849
    • Myers, C.J.1
  • 145
    • 77952851181 scopus 로고    scopus 로고
    • BoolNet-an R package for generation, reconstruction, and analysis of Boolean networks
    • Müssel, C. Hopfensitz, M. & Kestler, H. A. BoolNet-an R package for generation, reconstruction, and analysis of Boolean networks. Bioinformatics 26, 1378-1380 (2010).
    • (2010) Bioinformatics , vol.26 , pp. 1378-1380
    • Müssel Hopfensitz C, M.1    Kestler, H.A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.