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Volumn 25, Issue 6, 2009, Pages 801-807

Benchmarking regulatory network reconstruction with GRENDEL

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; AUTOMATION; COMPUTER MODEL; COMPUTER PROGRAM; COMPUTER SYSTEM; CONTROLLED STUDY; GENETIC ALGORITHM; GENETIC REGULATION; PRIORITY JOURNAL; QUALITY CONTROL;

EID: 62549091023     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btp068     Document Type: Article
Times cited : (24)

References (38)
  • 1
    • 13744265233 scopus 로고    scopus 로고
    • Extreme self-organization in networks constructed from gene expression data
    • Agrawal,H. (2002) Extreme self-organization in networks constructed from gene expression data. Am. Phy. Soc., 89, 268702.
    • (2002) Am. Phy. Soc , vol.89 , pp. 268702
    • Agrawal, H.1
  • 2
    • 33745449162 scopus 로고    scopus 로고
    • Comprehensive analysis of combinatorial regulation using the transcriptional regulatory network of yeast
    • Balaji,S. et al. (2006) Comprehensive analysis of combinatorial regulation using the transcriptional regulatory network of yeast. J. Mol. Biol., 360, 213-227.
    • (2006) J. Mol. Biol , vol.360 , pp. 213-227
    • Balaji, S.1
  • 3
    • 0038483826 scopus 로고    scopus 로고
    • Emergence of scaling in random networks
    • Barabasi,A.L. and Albert,R. (1999) Emergence of scaling in random networks. Science 286, 509-512.
    • (1999) Science , vol.286 , pp. 509-512
    • Barabasi, A.L.1    Albert, R.2
  • 4
    • 0742305866 scopus 로고    scopus 로고
    • Network biology: Understanding the cell's functional organization
    • Barabasi,A.L. and Oltvai,Z.N. (2004) Network biology: Understanding the cell's functional organization. Nat. Rev. Genet., 5, 101-113.
    • (2004) Nat. Rev. Genet , vol.5 , pp. 101-113
    • Barabasi, A.L.1    Oltvai, Z.N.2
  • 5
    • 33748377124 scopus 로고    scopus 로고
    • Quantification of protein half-lives in the budding yeast proteome
    • Belle,A. et al. (2006) Quantification of protein half-lives in the budding yeast proteome. Proc. Natl Acad. Sci., 103, 13004-13009.
    • (2006) Proc. Natl Acad. Sci , vol.103 , pp. 13004-13009
    • Belle, A.1
  • 6
    • 41849111321 scopus 로고    scopus 로고
    • Gene-network inference by message passing
    • Braunstein,A. et al. (2008) Gene-network inference by message passing. J. Phys., 95, 012016.
    • (2008) J. Phys , vol.95 , pp. 012016
    • Braunstein, A.1
  • 7
    • 41349112109 scopus 로고    scopus 로고
    • Rank-based edge reconstruction for scale-free genetic regulatory networks
    • Chen,G. et al. (2008) Rank-based edge reconstruction for scale-free genetic regulatory networks. BMC Bioinformatics, 9 75.
    • (2008) BMC Bioinformatics , vol.9 , pp. 75
    • Chen, G.1
  • 8
    • 46249103973 scopus 로고    scopus 로고
    • Stem cell transcriptome profiling via massive-scale mRNA sequencing
    • Cloonan,N. et al. (2008) Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nat. Meth., 5, 613-619.
    • (2008) Nat. Meth , vol.5 , pp. 613-619
    • Cloonan, N.1
  • 9
    • 12344321571 scopus 로고    scopus 로고
    • Discovery of meaningful associations in genomic data using partial correlation coefficients
    • de la Fuente,A. et al. (2004) Discovery of meaningful associations in genomic data using partial correlation coefficients. Bioinformatics, 20, 3565-3574.
    • (2004) Bioinformatics , vol.20 , pp. 3565-3574
    • de la Fuente, A.1
  • 10
    • 0032441150 scopus 로고    scopus 로고
    • Cluster analysis and display of genome-wide expression patterns
    • Eisen,M.B. et al. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci., 98, 14863-14868.
    • (1998) Proc. Natl Acad. Sci , vol.98 , pp. 14863-14868
    • Eisen, M.B.1
  • 11
    • 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. (2007) Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biol., 5, e8.
    • (2007) PLoS Biol , vol.5
    • Faith, J.J.1
  • 12
    • 62549119724 scopus 로고    scopus 로고
    • Funahashi,A. et al. (2003) CellDesigner: A process diagram editor for gene-regulatory and biochemical networks. Biosilico., 1, 159-162.
    • Funahashi,A. et al. (2003) CellDesigner: A process diagram editor for gene-regulatory and biochemical networks. Biosilico., 1, 159-162.
  • 13
    • 3242726930 scopus 로고    scopus 로고
    • Genomic run-on evaluates transcription rates for all yeast genes and identifies gene regulatory mechanisms
    • Garcia-Martinez,J. et al. (2004) Genomic run-on evaluates transcription rates for all yeast genes and identifies gene regulatory mechanisms. Mol. Cell, 15, 303-313.
    • (2004) Mol. Cell , vol.15 , pp. 303-313
    • Garcia-Martinez, J.1
  • 14
    • 0142215475 scopus 로고    scopus 로고
    • Global analysis of protein expression in yeast
    • Ghaemmaghami,S. et al. (2003) Global analysis of protein expression in yeast. Nature, 425, 737-741.
    • (2003) Nature , vol.425 , pp. 737-741
    • Ghaemmaghami, S.1
  • 15
    • 34249853738 scopus 로고    scopus 로고
    • Computational and experimental approaches for modeling gene regulatory networks
    • Goutsias,J. and Lee,N.H. (2007) Computational and experimental approaches for modeling gene regulatory networks. Curr. Pharm. Design 13, 1415-1436.
    • (2007) Curr. Pharm. Design , vol.13 , pp. 1415-1436
    • Goutsias, J.1    Lee, N.H.2
  • 16
    • 0033206211 scopus 로고    scopus 로고
    • Dynamical analysis of gene networks requires both mRNA and protein expression information
    • Hatzimanikatis,V. and Lee,K.H. (1999) Dynamical analysis of gene networks requires both mRNA and protein expression information. Met. Engr., 1, 275-281.
    • (1999) Met. Engr , vol.1 , pp. 275-281
    • Hatzimanikatis, V.1    Lee, K.H.2
  • 17
    • 0003043542 scopus 로고
    • The possible effects of the aggregation of the molecules of haemoglobin on its dissociation curves
    • Hill, A.V. (1910) The possible effects of the aggregation of the molecules of haemoglobin on its dissociation curves. J. Physiol., 40, iv-vii.
    • (1910) J. Physiol , vol.40
    • Hill, A.V.1
  • 18
    • 0030800564 scopus 로고    scopus 로고
    • The reversible Hill equation: How to incorporate cooperative enzymes into metabolic models
    • Hofmeyr,J.H.S. and Cornish-Bowden,H. (1997) The reversible Hill equation: How to incorporate cooperative enzymes into metabolic models. Bioinformatics, 13, 377-385.
    • (1997) Bioinformatics , vol.13 , pp. 377-385
    • Hofmeyr, J.H.S.1    Cornish-Bowden, H.2
  • 19
    • 0032567081 scopus 로고    scopus 로고
    • Dissecting the regulatory circuitry of a eukaryotic genome
    • Holstege,F.C. et al. (1998) Dissecting the regulatory circuitry of a eukaryotic genome. Cell, 95, 717-728.
    • (1998) Cell , vol.95 , pp. 717-728
    • Holstege, F.C.1
  • 20
    • 33845368513 scopus 로고    scopus 로고
    • COPASI- a complex pathway simulator
    • Hoops,S. et al. (2006) COPASI- a complex pathway simulator. Bioinformatics, 22, 3067-3074.
    • (2006) Bioinformatics , vol.22 , pp. 3067-3074
    • Hoops, S.1
  • 21
    • 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. (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics, 19, 524-531.
    • (2003) Bioinformatics , vol.19 , pp. 524-531
    • Hucka, M.1
  • 22
    • 0344464762 scopus 로고    scopus 로고
    • Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic bayesian networks
    • Husmeier,D. (2003) Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic bayesian networks. Bioinformatics, 19, 2271-2282.
    • (2003) Bioinformatics , vol.19 , pp. 2271-2282
    • Husmeier, D.1
  • 23
    • 18244384210 scopus 로고    scopus 로고
    • Multiple-laboratory comparison of microarray platforms
    • Irizarry,R.A. et al. (2005) Multiple-laboratory comparison of microarray platforms. Nat. Meth., 2, 345-350.
    • (2005) Nat. Meth , vol.2 , pp. 345-350
    • Irizarry, R.A.1
  • 24
    • 0842309206 scopus 로고    scopus 로고
    • Inferring gene networks from time series microarray data using dynamic Bayesian networks
    • Kim,S.Y. et al. (2003) Inferring gene networks from time series microarray data using dynamic Bayesian networks. Brief. Bioinform. 4, 228-235.
    • (2003) Brief. Bioinform , vol.4 , pp. 228-235
    • Kim, S.Y.1
  • 25
    • 3042799574 scopus 로고    scopus 로고
    • A computational algebra approach to the reverse engineering of gene regulatory networks
    • Laubenbacher,R. and Stigler,B. (2004) A computational algebra approach to the reverse engineering of gene regulatory networks. J. Theor. Biol., 229, 523-537.
    • (2004) J. Theor. Biol , vol.229 , pp. 523-537
    • Laubenbacher, R.1    Stigler, B.2
  • 26
    • 10544256600 scopus 로고    scopus 로고
    • Expression monitoring by hybridization to high-density oligonucleotide arrays
    • Lockhart,D.J. et al. (1996) Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat. Biotechnol., 14 1675-1680.
    • (1996) Nat. Biotechnol , vol.14 , pp. 1675-1680
    • Lockhart, D.J.1
  • 27
    • 33745631242 scopus 로고    scopus 로고
    • The SBML ODE solver library: A native API for symbolic and fast numerical analysis of reaction networks
    • Machne,R. et al. (2006) The SBML ODE solver library: A native API for symbolic and fast numerical analysis of reaction networks. Bioinformatics, 22, 1406-1407.
    • (2006) Bioinformatics , vol.22 , pp. 1406-1407
    • Machne, R.1
  • 28
    • 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. (2006) ARACNE: An algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics, 7, S7.
    • (2006) BMC Bioinformatics , vol.7
    • Margolin, A.A.1
  • 29
    • 2942694772 scopus 로고    scopus 로고
    • Artificial gene networks for objective comparison of analysis algorithms
    • Mendes,P. et al. (2003) Artificial gene networks for objective comparison of analysis algorithms. Bioinformatics, 19, 122-129.
    • (2003) Bioinformatics , vol.19 , pp. 122-129
    • Mendes, P.1
  • 30
    • 46249106990 scopus 로고    scopus 로고
    • Mapping and quantifying mammalian transcriptomes by RNA-Seq
    • Mortazavi,A. et al. (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Meth., 5, 621-628.
    • (2008) Nat. Meth , vol.5 , pp. 621-628
    • Mortazavi, A.1
  • 31
    • 17644396339 scopus 로고    scopus 로고
    • Dizzy: Stochastic simulation of large-scale genetic regulatory networks
    • Ramsey,S. et al. (2005) Dizzy: Stochastic simulation of large-scale genetic regulatory networks. J. Bioinform. Comput. Biol. 3, 415-436.
    • (2005) J. Bioinform. Comput. Biol , vol.3 , pp. 415-436
    • Ramsey, S.1
  • 32
    • 0028806048 scopus 로고
    • Quantitative monitoring of gene expression patterns with a complementary DNA microarray
    • Schena,M. et al. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 270, 467-470.
    • (1995) Science , vol.270 , pp. 467-470
    • Schena, M.1
  • 33
    • 0036578795 scopus 로고    scopus 로고
    • Network motifs in the transcriptional network or Escherichia coli
    • Shen-Orr,S.S. et al. (2002) Network motifs in the transcriptional network or Escherichia coli. Nat. Genet., 31, 64-68.
    • (2002) Nat. Genet , vol.31 , pp. 64-68
    • Shen-Orr, S.S.1
  • 34
    • 0041627865 scopus 로고    scopus 로고
    • Influence of network topology and data collection on network inference
    • Smith,V.A. et al. (2003) Influence of network topology and data collection on network inference. Pac. Symp. Biocomput., 164-175.
    • (2003) Pac. Symp. Biocomput , pp. 164-175
    • Smith, V.A.1
  • 35
    • 36249019789 scopus 로고    scopus 로고
    • Dialogue on reverse-engineering assessment and methods: The DREAM of high-throughput pathway inference
    • Stolovitzky,G. et al. (2007) Dialogue on reverse-engineering assessment and methods: The DREAM of high-throughput pathway inference. Ann. NY Acad. Sci., 1115, 1-22.
    • (2007) Ann. NY Acad. Sci , vol.1115 , pp. 1-22
    • Stolovitzky, G.1
  • 36
    • 62549090335 scopus 로고    scopus 로고
    • From specific gene regulation to genomic networks: A global analysis of transcriptional regulation en Escherichia coli
    • Thieffry,D. et al. (1998) From specific gene regulation to genomic networks: A global analysis of transcriptional regulation en Escherichia coli. Bioessays, 50, 49-59.
    • (1998) Bioessays , vol.50 , pp. 49-59
    • Thieffry, D.1
  • 37
    • 33144486498 scopus 로고    scopus 로고
    • SynTReN: A generator of synthetic gene expression data for design and analysis of structure learning algorithms
    • Van den Bulcke,T. et al. (2006) SynTReN: A generator of synthetic gene expression data for design and analysis of structure learning algorithms. BMC Bioinformatics, 7, 43.
    • (2006) BMC Bioinformatics , vol.7 , pp. 43
    • Van den Bulcke, T.1
  • 38
    • 0242651270 scopus 로고    scopus 로고
    • Simulation studies for the identification of genetic networks from cDNAarray and regulatory activity data
    • Caltech, Pasedena, CA, pp
    • Zak,D.E. et al. (2001) Simulation studies for the identification of genetic networks from cDNAarray and regulatory activity data. In Proceedings of the Second International Conference on Systems Biology Caltech, Pasedena, CA, pp. 231-238.
    • (2001) Proceedings of the Second International Conference on Systems Biology , pp. 231-238
    • Zak, D.E.1


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