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Volumn 4, Issue JUN, 2013, Pages

Modeling regulatory cascades using artificial neural networks: The case of transcriptional regulatory networks shaped during the yeast stress response

Author keywords

Artificial Neural Networks; Asynchronous regulation; Heterodimers; Three layers regulatory cascades; Transcriptional regulatory networks; Yeast stress response

Indexed keywords


EID: 84883547999     PISSN: None     EISSN: 16648021     Source Type: Journal    
DOI: 10.3389/fgene.2013.00110     Document Type: Article
Times cited : (6)

References (69)
  • 1
    • 43849088207 scopus 로고    scopus 로고
    • Choose your partners: dimerization in eukaryotic transcription factors
    • doi: 10.1016/j.tibs.2008.02.002
    • Amoutzias, G. D., Robertson, D. L., Van De Peer, Y., and Oliver, S. G. (2008). Choose your partners: dimerization in eukaryotic transcription factors. Trends Biochem. Sci. 33, 220-229. doi: 10.1016/j.tibs.2008.02.002
    • (2008) Trends Biochem. Sci. , vol.33 , pp. 220-229
    • Amoutzias, G.D.1    Robertson, D.L.2    Van De Peer, Y.3    Oliver, S.G.4
  • 2
    • 0027306799 scopus 로고
    • Genetics of eukaryotic RNA polymerases I, II, and III
    • Archambault, J., and Friesen, J. D. (1993). Genetics of eukaryotic RNA polymerases I, II, and III. Microbiol. Rev. 57, 703-724.
    • (1993) Microbiol. Rev. , vol.57 , pp. 703-724
    • Archambault, J.1    Friesen, J.D.2
  • 3
    • 0034101979 scopus 로고    scopus 로고
    • Genome-wide expression patterns in Saccharomyces cerevisiae: comparison of drug treatments and genetic alterations affecting biosynthesis of ergosterol
    • doi: 10.1128/AAC.44.5.1255-1265.2000
    • Bammert, G. F., and Fostel, J. M. (2000). Genome-wide expression patterns in Saccharomyces cerevisiae: comparison of drug treatments and genetic alterations affecting biosynthesis of ergosterol. Antimicrobial Agents Chemother. 44, 1255-1265. doi: 10.1128/AAC.44.5.1255-1265.2000
    • (2000) Antimicrobial Agents Chemother. , vol.44 , pp. 1255-1265
    • Bammert, G.F.1    Fostel, J.M.2
  • 4
    • 10744226222 scopus 로고    scopus 로고
    • Computational discovery of gene modules and regulatory networks
    • doi: 10.1038/nbt890
    • Bar-Joseph, Z., Gerber, G. K., Lee, T. I., Rinaldi, N. J., Yoo, J. Y., Robert, F., et al. (2003). Computational discovery of gene modules and regulatory networks. Nat. Biotechnol. 21, 1337-1342. doi: 10.1038/nbt890
    • (2003) Nat. Biotechnol. , vol.21 , pp. 1337-1342
    • Bar-Joseph, Z.1    Gerber, G.K.2    Lee, T.I.3    Rinaldi, N.J.4    Yoo, J.Y.5    Robert, F.6
  • 5
    • 65149105339 scopus 로고    scopus 로고
    • A post-translational modification code for transcription factors: sorting through a sea of signals
    • doi: 10.1016/j.tcb.2009.02.003
    • Benayoun, B. A., and Veitia, R. A. (2009). A post-translational modification code for transcription factors: sorting through a sea of signals. Trends Cell Biol. 19, 189-197. doi: 10.1016/j.tcb.2009.02.003
    • (2009) Trends Cell Biol. , vol.19 , pp. 189-197
    • Benayoun, B.A.1    Veitia, R.A.2
  • 6
    • 34249041230 scopus 로고    scopus 로고
    • Exploring genetic interactions and networks with yeast
    • doi: 10.1038/nrg2085
    • Boone, C., Bussey, H., and Andrews, B. J. (2007). Exploring genetic interactions and networks with yeast. Nat. Rev. Genet. 8, 437-449. doi: 10.1038/nrg2085
    • (2007) Nat. Rev. Genet. , vol.8 , pp. 437-449
    • Boone, C.1    Bussey, H.2    Andrews, B.J.3
  • 7
    • 46249112705 scopus 로고    scopus 로고
    • Boolean network models of cellular regulation: prospects and limitations
    • doi: 10.1098/rsif.2008.0132.focus
    • Bornholdt, S. (2008). Boolean network models of cellular regulation: prospects and limitations. J. R. Soc. Interface 6, S85-S94. doi: 10.1098/rsif.2008.0132.focus
    • (2008) J. R. Soc. Interface , vol.6
    • Bornholdt, S.1
  • 8
    • 0030768919 scopus 로고    scopus 로고
    • Yeast as a model organism
    • doi: 10.1126/science.277.5330.1259
    • Botstein, D., Chervitz, S. A., and Michael, C. (1997). Yeast as a model organism. Science 277, 1259-1260. doi: 10.1126/science.277.5330.1259
    • (1997) Science , vol.277 , pp. 1259-1260
    • Botstein, D.1    Chervitz, S.A.2    Michael, C.3
  • 9
    • 56449094227 scopus 로고    scopus 로고
    • Control, responses and modularity of cellular regulatory networks: a control analysis perspective
    • doi: 10.1049/iet-syb:20070065
    • Bruggeman, F. J., Snoep, J. L., and Westerhoff, H. V. (2008). Control, responses and modularity of cellular regulatory networks: a control analysis perspective. IET Syst. Biol. 2, 397-410. doi: 10.1049/iet-syb:20070065
    • (2008) IET Syst. Biol. , vol.2 , pp. 397-410
    • Bruggeman, F.J.1    Snoep, J.L.2    Westerhoff, H.V.3
  • 10
  • 11
    • 0032450984 scopus 로고    scopus 로고
    • The yeast RNA polymerase III transcription machinery: a paradigm for eukaryotic gene activation
    • doi: 10.1101/sqb.1998.63.381
    • Chédin, S., Ferri, M. L., Peyroche, G., Andrau, J. C., Jourdain, S., Lefebvre, O., et al. (1998). The yeast RNA polymerase III transcription machinery: a paradigm for eukaryotic gene activation. Cold Spring Harb. Symp. Quant. Biol. 63, 381-389. doi: 10.1101/sqb.1998.63.381
    • (1998) Cold Spring Harb. Symp. Quant. Biol. , vol.63 , pp. 381-389
    • Chédin, S.1    Ferri, M.L.2    Peyroche, G.3    Andrau, J.C.4    Jourdain, S.5    Lefebvre, O.6
  • 12
    • 34147179823 scopus 로고    scopus 로고
    • Clustering of genes into regulons using integrated modeling-COGRIM
    • doi: 10.1186/gb-2007-8-1-r4
    • Chen, G., Jensen, S. T., and Stoeckert, C. J. (2007). Clustering of genes into regulons using integrated modeling-COGRIM. Genome Biol. 8, R4. doi: 10.1186/gb-2007-8-1-r4
    • (2007) Genome Biol. , vol.8
    • Chen, G.1    Jensen, S.T.2    Stoeckert, C.J.3
  • 13
    • 0033780450 scopus 로고    scopus 로고
    • A computational analysis of whole-genome expression data reveals chromosomal domains of gene expression
    • doi: 10.1038/79896
    • Cohen, B. A., Mitra, R. D., Hughes, J. D., and Church, G. M. (2000). A computational analysis of whole-genome expression data reveals chromosomal domains of gene expression. Nat. Genet. 26, 183-186. doi: 10.1038/79896
    • (2000) Nat. Genet. , vol.26 , pp. 183-186
    • Cohen, B.A.1    Mitra, R.D.2    Hughes, J.D.3    Church, G.M.4
  • 14
    • 0026755390 scopus 로고
    • Coregulation of purine and histidine biosynthesis by the transcriptional activators BAS1 and BAS2
    • doi: 10.1073/pnas.89.15.6746
    • Daignan-Fornier, B., and Fink, G. R. (1992). Coregulation of purine and histidine biosynthesis by the transcriptional activators BAS1 and BAS2. Proc. Natl. Acad. Sci. U.S.A. 89, 6746-6750. doi: 10.1073/pnas.89.15.6746
    • (1992) Proc. Natl. Acad. Sci. U.S.A. , vol.89 , pp. 6746-6750
    • Daignan-Fornier, B.1    Fink, G.R.2
  • 15
    • 0031886352 scopus 로고    scopus 로고
    • Functional dissection of yeast Hir1p, a WD repeat-containing transcriptional corepressor
    • Desilva, H., Lee, K., and Osley, M. A. (1998). Functional dissection of yeast Hir1p, a WD repeat-containing transcriptional corepressor. Genetics 148, 657-667.
    • (1998) Genetics , vol.148 , pp. 657-667
    • Desilva, H.1    Lee, K.2    Osley, M.A.3
  • 17
    • 36949004555 scopus 로고    scopus 로고
    • Molecular basis for evolving modularity in the yeast protein interaction network
    • doi: 10.1371/journal.pcbi.0030226
    • Fernández, A. (2007). Molecular basis for evolving modularity in the yeast protein interaction network. PLoS Comput. Biol. 3 ,e226. doi: 10.1371/journal.pcbi.0030226
    • (2007) PLoS Comput. Biol. , vol.3
    • Fernández, A.1
  • 18
    • 25444481571 scopus 로고    scopus 로고
    • Scoring functions for transcription factor binding site prediction
    • doi: 10.1186/1471-2105-6-84
    • Friberg, M., Von Rohr, P., and Gonnet, G. (2005). Scoring functions for transcription factor binding site prediction. BMC Bioinformatics 6, 84. doi: 10.1186/1471-2105-6-84
    • (2005) BMC Bioinformatics , vol.6 , pp. 84
    • Friberg, M.1    Von Rohr, P.2    Gonnet, G.3
  • 19
    • 2942582468 scopus 로고    scopus 로고
    • Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data
    • doi: 10.1186/1471-2105-5-31
    • Gao, F., Foat, B. C., and Bussemaker, H. J. (2004). Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data. BMC Bioinformatics 5, 31. doi: 10.1186/1471-2105-5-31
    • (2004) BMC Bioinformatics , vol.5 , pp. 31
    • Gao, F.1    Foat, B.C.2    Bussemaker, H.J.3
  • 20
    • 0033637153 scopus 로고    scopus 로고
    • Genomic expression programs in the response of yeast cells to environmental changes
    • Gasch, A. P., Spellman, P. T., Kao, C. M., Carmel-Harel, O., Eisen, M. B., Storz, G., et al. (2000). Genomic expression programs in the response of yeast cells to environmental changes. Mol. Biol. Cell 11, 4241-4257.
    • (2000) Mol. Biol. Cell , vol.11 , pp. 4241-4257
    • Gasch, A.P.1    Spellman, P.T.2    Kao, C.M.3    Carmel-Harel, O.4    Eisen, M.B.5    Storz, G.6
  • 21
    • 0036728274 scopus 로고    scopus 로고
    • The genomics of yeast responses to environmental stress and starvation
    • doi: 10.1007/s10142-002-0058-2
    • Gasch, A. P., and Werner-Washburne, M. (2002). The genomics of yeast responses to environmental stress and starvation. Funct. Integr. Genomics 2, 181-192. doi: 10.1007/s10142-002-0058-2
    • (2002) Funct. Integr. Genomics , vol.2 , pp. 181-192
    • Gasch, A.P.1    Werner-Washburne, M.2
  • 22
    • 0035967858 scopus 로고    scopus 로고
    • The RNA polymerase III transcription apparatus
    • doi: 10.1006/jmbi.2001.4732
    • Geiduschek, E. P., and Kassavetis, G. A. (2001). The RNA polymerase III transcription apparatus. J. Mol. Biol. 29, 1-26. doi: 10.1006/jmbi.2001.4732
    • (2001) J. Mol. Biol. , vol.29 , pp. 1-26
    • Geiduschek, E.P.1    Kassavetis, G.A.2
  • 23
    • 38849086867 scopus 로고    scopus 로고
    • Rsp5 is required for the nuclear export of mRNA of HSF1 and MSN2/4 under stress conditions in Saccharomyces cerevisiae
    • doi: 10.1111/j.1365-2443.2007.01154.x
    • Haitani, Y., and Takagi, H. (2008). Rsp5 is required for the nuclear export of mRNA of HSF1 and MSN2/4 under stress conditions in Saccharomyces cerevisiae. Genes Cells 13, 105-116. doi: 10.1111/j.1365-2443.2007.01154.x
    • (2008) Genes Cells , vol.13 , pp. 105-116
    • Haitani, Y.1    Takagi, H.2
  • 24
    • 38849146505 scopus 로고    scopus 로고
    • Understanding biological functions through molecular networks
    • doi: 10.1038/cr.2008.16
    • Han, J. (2008). Understanding biological functions through molecular networks. Cell Res. 18, 224-237. doi: 10.1038/cr.2008.16
    • (2008) Cell Res. , vol.18 , pp. 224-237
    • Han, J.1
  • 25
    • 4544352942 scopus 로고    scopus 로고
    • Transcriptional regulatory code of a eukaryotic genome
    • doi: 10.1038/nature02800
    • Harbison, C. T., Gordon, D. B., Lee, T. I., Rinaldi, N. J., Macisaac, K. D., Danford, T. W., et al. (2004). Transcriptional regulatory code of a eukaryotic genome. Nature 431, 99-104. doi: 10.1038/nature02800
    • (2004) Nature , vol.431 , pp. 99-104
    • Harbison, C.T.1    Gordon, D.B.2    Lee, T.I.3    Rinaldi, N.J.4    Macisaac, K.D.5    Danford, T.W.6
  • 26
    • 33846013249 scopus 로고    scopus 로고
    • Connectivity in the yeast cell cycle transcription network: inferences from neural networks
    • doi: 10.1371/journal.pcbi.0020169
    • Hart, C. E., Mjolsness, E., and Wold, B. J. (2006). Connectivity in the yeast cell cycle transcription network: inferences from neural networks. PLoS Comput. Biol. 2 ,e169. doi: 10.1371/journal.pcbi.0020169
    • (2006) PLoS Comput. Biol. , vol.2
    • Hart, C.E.1    Mjolsness, E.2    Wold, B.J.3
  • 27
    • 0033518234 scopus 로고    scopus 로고
    • From molecular to modular cell biology
    • doi: 10.1038/35011540
    • Hartwell, L. H., Hopfield, J. J., Leibler, S., and Murray, A. W. (1999). From molecular to modular cell biology. Nature 402, C47-C52. doi: 10.1038/35011540
    • (1999) Nature , vol.402
    • Hartwell, L.H.1    Hopfield, J.J.2    Leibler, S.3    Murray, A.W.4
  • 28
    • 38349026526 scopus 로고    scopus 로고
    • Dynamic cumulative activity of transcription factors as a mechanism of quantitative gene regulation
    • doi: 10.1186/gb-2007-8-9-r181
    • He, F., Buer, J., Zeng, A. P., and Balling, R. (2007). Dynamic cumulative activity of transcription factors as a mechanism of quantitative gene regulation. Genome Biol. 8, R181. doi: 10.1186/gb-2007-8-9-r181
    • (2007) Genome Biol. , vol.8
    • He, F.1    Buer, J.2    Zeng, A.P.3    Balling, R.4
  • 29
    • 33645784574 scopus 로고    scopus 로고
    • In search of functional association from time-series microarray data based on the change trend and level of gene expression
    • doi: 10.1186/1471-2105-7-69
    • He, F., and Zeng, A. P. (2006). In search of functional association from time-series microarray data based on the change trend and level of gene expression. BMC Bioinformatics 7 ,69. doi: 10.1186/1471-2105-7-69
    • (2006) BMC Bioinformatics , vol.7 , pp. 69
    • He, F.1    Zeng, A.P.2
  • 30
    • 61349180117 scopus 로고    scopus 로고
    • Gene regulatory network inference: data integration in dynamic models-a review
    • doi: 10.1016/j.biosystems.2008.12.004
    • Hecker, M., Lambeck, S., Toepfer, S., Van Someren, E., and Guthke, R. (2009). Gene regulatory network inference: data integration in dynamic models-a review. BioSystems 96, 86-103. doi: 10.1016/j.biosystems.2008.12.004
    • (2009) BioSystems , vol.96 , pp. 86-103
    • Hecker, M.1    Lambeck, S.2    Toepfer, S.3    Van Someren, E.4    Guthke, R.5
  • 31
    • 0034682504 scopus 로고    scopus 로고
    • Fundamental patterns underlying gene expression profiles: simplicity from complexity
    • doi: 10.1073/pnas.150242097
    • Holter, N. S., Mitra, M., Maritan, A., Cieplak, M., Banavar, J. R., and Fedoroff, N. V. (2000). Fundamental patterns underlying gene expression profiles: simplicity from complexity. Proc. Natl. Acad. Sci. U.S.A. 97, 8409-8414. doi: 10.1073/pnas.150242097
    • (2000) Proc. Natl. Acad. Sci. U.S.A. , vol.97 , pp. 8409-8414
    • Holter, N.S.1    Mitra, M.2    Maritan, A.3    Cieplak, M.4    Banavar, J.R.5    Fedoroff, N.V.6
  • 32
    • 48349124629 scopus 로고    scopus 로고
    • MOPAT: a graph-based method to predict recurrent cis-regulatory modules from known motifs
    • doi: 10.1093/nar/gkn407
    • Hu J., Hu, H., and Li, X. (2008). MOPAT: a graph-based method to predict recurrent cis-regulatory modules from known motifs. Nucleic Acids Res. 36, 4488-4497. doi: 10.1093/nar/gkn407
    • (2008) Nucleic Acids Res. , vol.36 , pp. 4488-4497
    • Hu, J.1    Hu, H.2    Li, X.3
  • 33
    • 0348013431 scopus 로고    scopus 로고
    • Clustering gene expression pattern and extracting relationship in gene network based on artificial neural networks
    • Huang, J., Shimizu, H., and Shioya, S. (2003). Clustering gene expression pattern and extracting relationship in gene network based on artificial neural networks. J. Biosci. Bioeng. 96, 421-428.
    • (2003) J. Biosci. Bioeng. , vol.96 , pp. 421-428
    • Huang, J.1    Shimizu, H.2    Shioya, S.3
  • 34
    • 0346095291 scopus 로고    scopus 로고
    • Principles of transcriptional control in the metabolic network of Saccharomyces cerevisiae
    • doi: 10.1038/nbt918
    • Ihmels, J., Levy, R., and Barkai, N. (2004). Principles of transcriptional control in the metabolic network of Saccharomyces cerevisiae. Nat. Biotechnol. 22, 86-92. doi: 10.1038/nbt918
    • (2004) Nat. Biotechnol. , vol.22 , pp. 86-92
    • Ihmels, J.1    Levy, R.2    Barkai, N.3
  • 35
    • 3242875300 scopus 로고    scopus 로고
    • Combining microarrays and biological knowledge for estimating gene networks via bayesian networks
    • doi: 10.1142/S021972000400048X
    • Imoto, S., Higuchi, T., Goto, T., Tashiro, K., Kuhara, S., and Miyano, S. (2004). Combining microarrays and biological knowledge for estimating gene networks via bayesian networks. J. Bioinform. Comput. Biol. 2, 77-98. doi: 10.1142/S021972000400048X
    • (2004) J. Bioinform. Comput. Biol. , vol.2 , pp. 77-98
    • Imoto, S.1    Higuchi, T.2    Goto, T.3    Tashiro, K.4    Kuhara, S.5    Miyano, S.6
  • 36
    • 3042698613 scopus 로고    scopus 로고
    • Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network
    • doi: 10.1142/S0219720003000071
    • Imoto, S., Kim, S., Goto, T., Miyano, S., Aburatani, S., Tashiro, K., et al. (2003). Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network. J. Bioinform. Comput. Biol. 1, 231-252. doi: 10.1142/S0219720003000071
    • (2003) J. Bioinform. Comput. Biol. , vol.1 , pp. 231-252
    • Imoto, S.1    Kim, S.2    Goto, T.3    Miyano, S.4    Aburatani, S.5    Tashiro, K.6
  • 37
    • 79960901603 scopus 로고    scopus 로고
    • Reconstructing regulatory network transitions
    • doi: 10.1016/j.tcb.2011.05.001
    • Petricka, J. J., and Benfey, P. N. (2011). Reconstructing regulatory network transitions. Trends Cell Biol. 21, 442-451. doi: 10.1016/j.tcb.2011.05.001
    • (2011) Trends Cell Biol. , vol.21 , pp. 442-451
    • Petricka, J.J.1    Benfey, P.N.2
  • 38
    • 33846048300 scopus 로고    scopus 로고
    • When transcriptome meets metabolome: fast cellular responses of yeast to sudden relief of glucose limitation
    • doi: 10.1038/msb4100083
    • Kresnowati, M. T., Van Winden, W. A., Almering, M. J., Ten Pierick, A., Ras, C., Knijnenburg, T. A., et al. (2006). When transcriptome meets metabolome: fast cellular responses of yeast to sudden relief of glucose limitation. Mol. Syst. Biol. 2, 49. doi: 10.1038/msb4100083
    • (2006) Mol. Syst. Biol. , vol.2 , pp. 49
    • Kresnowati, M.T.1    Van Winden, W.A.2    Almering, M.J.3    Ten Pierick, A.4    Ras, C.5    Knijnenburg, T.A.6
  • 39
    • 27644466832 scopus 로고    scopus 로고
    • Combining sequence and time series expression data to learn transcriptional modules
    • doi: 10.1109/TCBB.2005.34
    • Kundaje, A., Middendorf, M., Gao, F., Wiggins, C., and Leslie, C. (2005). Combining sequence and time series expression data to learn transcriptional modules. IEEE/ACM Trans. Comput. Biol. Bioinform. 2, 194-202. doi: 10.1109/TCBB.2005.34
    • (2005) IEEE/ACM Trans. Comput. Biol. Bioinform. , vol.2 , pp. 194-202
    • Kundaje, A.1    Middendorf, M.2    Gao, F.3    Wiggins, C.4    Leslie, C.5
  • 40
    • 0036135461 scopus 로고    scopus 로고
    • Genomic analyses of anaerobically induced genes in Saccharomyces cerevisiae: functional roles of Rox1 and other factors in mediating the anoxic response
    • doi: 10.1128/JB.184.1.250-265.2002
    • Kwast, K. E., Lai, L. C., Menda, N., James, D. T. 3rd., Aref, S., and Burke, P. V. (2002). Genomic analyses of anaerobically induced genes in Saccharomyces cerevisiae: functional roles of Rox1 and other factors in mediating the anoxic response. J. Bacteriol. 184, 250-265. doi: 10.1128/JB.184.1.250-265.2002
    • (2002) J. Bacteriol. , vol.184 , pp. 250-265
    • Kwast, K.E.1    Lai, L.C.2    Menda, N.3    James, D.T.4    Aref, S.5    Burke, P.V.6
  • 41
    • 46249096061 scopus 로고    scopus 로고
    • High-resolution analysis of condition-specific regulatory modules in Saccharomyces cerevisiae
    • doi: 10.1186/gb-2008-9-1-r2
    • Lee, H.-G., Lee, H.-S., Jeon, S.-H., Chung, T.-H., Young-Sung, L., and Won-Ki, H. (2008). High-resolution analysis of condition-specific regulatory modules in Saccharomyces cerevisiae. Genome Biol. 9, doi: 10.1186/gb-2008-9-1-r2
    • (2008) Genome Biol. , pp. 9
    • Lee, H.-G.1    Lee, H.-S.2    Jeon, S.-H.3    Chung, T.-H.4    Young-Sung, L.5    Won-Ki, H.6
  • 42
    • 0037174671 scopus 로고    scopus 로고
    • Transcriptional regulatory networks in Saccharomyces cerevisiae
    • doi: 10.1126/science.1075090
    • Lee, T. I., Rinaldi, N. J., Robert, F., Odom, D. T., Bar-Joseph, Z., Gerber, G. K., et al. (2002). Transcriptional regulatory networks in Saccharomyces cerevisiae. Science 298, 799-804. doi: 10.1126/science.1075090
    • (2002) Science , vol.298 , pp. 799-804
    • Lee, T.I.1    Rinaldi, N.J.2    Robert, F.3    Odom, D.T.4    Bar-Joseph, Z.5    Gerber, G.K.6
  • 43
    • 0000873069 scopus 로고
    • A method for the solution of certain non-linear problems in least squares
    • Levenberg, K. (1944). A method for the solution of certain non-linear problems in least squares. Q. Appl. Math. 2, 164-168.
    • (1944) Q. Appl. Math. , vol.2 , pp. 164-168
    • Levenberg, K.1
  • 44
    • 0036166753 scopus 로고    scopus 로고
    • Linear modes of gene expression determined by independent component analysis
    • doi: 10.1093/bioinformatics/18.1.51
    • Liebermeister, W. (2002). Linear modes of gene expression determined by independent component analysis. Bioinformatics 18, 51-60. doi: 10.1093/bioinformatics/18.1.51
    • (2002) Bioinformatics , vol.18 , pp. 51-60
    • Liebermeister, W.1
  • 45
    • 38549168494 scopus 로고    scopus 로고
    • Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory
    • doi: 10.1186/1471-2105-8-299
    • Luo, F., Yang, Y., Zhong, J., Gao, H., Khan, L., Thompson, D. K., et al. (2007). Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory. BMC Bioinformatics 8, 299. doi: 10.1186/1471-2105-8-299
    • (2007) BMC Bioinformatics , vol.8 , pp. 299
    • Luo, F.1    Yang, Y.2    Zhong, J.3    Gao, H.4    Khan, L.5    Thompson, D.K.6
  • 46
    • 57749210454 scopus 로고    scopus 로고
    • An in silico method for detecting overlapping functional modules from composite biological networks
    • doi: 10.1186/1752-0509-2-93
    • Maraziotis, I., Dimitrakopoulou, K., and Bezerianos, A. (2008). An in silico method for detecting overlapping functional modules from composite biological networks. BMC. Syst. Biol. 2, 93. doi: 10.1186/1752-0509-2-93
    • (2008) BMC. Syst. Biol. , vol.2 , pp. 93
    • Maraziotis, I.1    Dimitrakopoulou, K.2    Bezerianos, A.3
  • 47
    • 0000169232 scopus 로고
    • An algorithm for least-squares estimation of nonlinear parameters
    • doi: 10.1137/0111030
    • Marquardt, D. W. (1963). An algorithm for least-squares estimation of nonlinear parameters. J. Soc. Ind. Appl. Math. 11, 431-441. doi: 10.1137/0111030
    • (1963) J. Soc. Ind. Appl. Math. , vol.11 , pp. 431-441
    • Marquardt, D.W.1
  • 48
    • 0029879360 scopus 로고    scopus 로고
    • The Saccharomyces cerevisiae zinc finger proteins Msn2p and Msn4p are required for transcriptional induction through the stress response element (STRE)
    • Martinez-Pastor, M. T., Marchler, G., Schuller, C., Marchler-Bauer, A., Ruis, H., and Estruch, F. (1996). The Saccharomyces cerevisiae zinc finger proteins Msn2p and Msn4p are required for transcriptional induction through the stress response element (STRE). EMBO J. 15, 2227-2235.
    • (1996) EMBO J. , vol.15 , pp. 2227-2235
    • Martinez-Pastor, M.T.1    Marchler, G.2    Schuller, C.3    Marchler-Bauer, A.4    Ruis, H.5    Estruch, F.6
  • 49
    • 35348813628 scopus 로고    scopus 로고
    • Propagation of large concentration changes in reversible protein-binding networks
    • doi: 10.1073/pnas.0702905104
    • Maslov, S., and Ispolatov, I. (2007). Propagation of large concentration changes in reversible protein-binding networks. Proc. Natl. Acad. Sci. U.S.A. 104, 13655-13660. doi: 10.1073/pnas.0702905104
    • (2007) Proc. Natl. Acad. Sci. U.S.A. , vol.104 , pp. 13655-13660
    • Maslov, S.1    Ispolatov, I.2
  • 50
    • 0030765448 scopus 로고    scopus 로고
    • MIPS: a database for protein sequences, homology data and yeast genome information
    • doi: 10.1093/nar/25.1.28
    • Mewes, H. W., Albermann, K., Heumann, K., Liebl, S., and Pfeiffer, F. (1997). MIPS: a database for protein sequences, homology data and yeast genome information. Nucleic Acids Res. 25, 28-30. doi: 10.1093/nar/25.1.28
    • (1997) Nucleic Acids Res. , vol.25 , pp. 28-30
    • Mewes, H.W.1    Albermann, K.2    Heumann, K.3    Liebl, S.4    Pfeiffer, F.5
  • 51
    • 33846624274 scopus 로고    scopus 로고
    • Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering
    • doi: 10.1186/1471-2105-8-5
    • Pal, N. R., Aguan, K., Sharma, A., and Amari, S. (2007). Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering. BMC Bioinformatics 8, 5. doi: 10.1186/1471-2105-8-5
    • (2007) BMC Bioinformatics , vol.8 , pp. 5
    • Pal, N.R.1    Aguan, K.2    Sharma, A.3    Amari, S.4
  • 52
    • 33947409985 scopus 로고    scopus 로고
    • Factor analysis for gene regulatory networks and transcription factor activity profiles
    • doi: 10.1186/1471-2105-8-61
    • Pournara, I., and Wernisch, L. (2007). Factor analysis for gene regulatory networks and transcription factor activity profiles. BMC Bioinformatics 8, 61. doi: 10.1186/1471-2105-8-61
    • (2007) BMC Bioinformatics , vol.8 , pp. 61
    • Pournara, I.1    Wernisch, L.2
  • 54
    • 0034863951 scopus 로고    scopus 로고
    • "Inferring a system of differential equations for a gene regulatory network by using genetic programming" in Evolutionary Computation 2001
    • Seoul
    • Sakamoto, E., and Iba, H. (2001). "Inferring a system of differential equations for a gene regulatory network by using genetic programming" in Evolutionary Computation 2001. Proceedings of the 2001 Congress on, Vol. 1 (Seoul), 720-726.
    • (2001) Proceedings of the 2001 Congress on , vol.1 , pp. 720-726
    • Sakamoto, E.1    Iba, H.2
  • 55
    • 0037941585 scopus 로고    scopus 로고
    • Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data
    • Segal, E., Shapira, M., Regev, A., Pe'er, D., Botstein, D., Koller, D., et al. (2003). Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. Nat. Genet. 34, 166-176.
    • (2003) Nat. Genet. , vol.34 , pp. 166-176
    • Segal, E.1    Shapira, M.2    Regev, A.3    Pe'er, D.4    Botstein, D.5    Koller, D.6
  • 56
    • 84871839544 scopus 로고    scopus 로고
    • Gene expression based leukemia sub-classification using committee neural networks
    • Sewak, M. S., Narender, P. R., and Duan, Z. H. (2009). Gene expression based leukemia sub-classification using committee neural networks. Bioinform. Biol. Insights 3, 89-98.
    • (2009) Bioinform. Biol. Insights , vol.3 , pp. 89-98
    • Sewak, M.S.1    Narender, P.R.2    Duan, Z.H.3
  • 57
    • 0027391029 scopus 로고
    • Characterization of HIR1 and HIR2, two genes required for regulation of histone gene transcription in Saccharomyces cerevisiae
    • Sherwood, P. W., Tsang, S. V., and Osley, M. A. (1993). Characterization of HIR1 and HIR2, two genes required for regulation of histone gene transcription in Saccharomyces cerevisiae. Mol. Cell. Biol. 13, 28-38.
    • (1993) Mol. Cell. Biol. , vol.13 , pp. 28-38
    • Sherwood, P.W.1    Tsang, S.V.2    Osley, M.A.3
  • 58
    • 26944450884 scopus 로고    scopus 로고
    • DNA-bound Bas1 recruits Pho2 to activate ADE genes in Saccharomyces cerevisiae
    • doi: 10.1128/EC.4.10.1725-1735.2005
    • Som, I., Mitsch, R. N., Urbanowski, J. L., and Rolfes, R. J. (2005). DNA-bound Bas1 recruits Pho2 to activate ADE genes in Saccharomyces cerevisiae. Eukaryotic Cell 4, 1725-1735. doi: 10.1128/EC.4.10.1725-1735.2005
    • (2005) Eukaryotic Cell , vol.4 , pp. 1725-1735
    • Som, I.1    Mitsch, R.N.2    Urbanowski, J.L.3    Rolfes, R.J.4
  • 59
    • 1542357674 scopus 로고    scopus 로고
    • Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data
    • doi: 10.1073/pnas.0308661100
    • Tanay, A., Sharan, R., Kupiec, M., and Shamir, R. (2004). Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data. Proc. Natl. Acad. Sci. U.S.A. 101, 2981-2986. doi: 10.1073/pnas.0308661100
    • (2004) Proc. Natl. Acad. Sci. U.S.A. , vol.101 , pp. 2981-2986
    • Tanay, A.1    Sharan, R.2    Kupiec, M.3    Shamir, R.4
  • 60
    • 0024391094 scopus 로고
    • BAS1 has a Myb motif and activates HIS4 transcription only in combination with BAS2
    • doi: 10.1126/science.2683089
    • Tice-Baldwin, K., Fink, G. R., and Arndt, K. T. (1989). BAS1 has a Myb motif and activates HIS4 transcription only in combination with BAS2. Science 246, 931-935. doi: 10.1126/science.2683089
    • (1989) Science , vol.246 , pp. 931-935
    • Tice-Baldwin, K.1    Fink, G.R.2    Arndt, K.T.3
  • 61
    • 0345305369 scopus 로고    scopus 로고
    • Functional modules by relating protein interaction networks and gene expression
    • doi: 10.1093/nar/gkg838
    • Tornow, S., and Mewes, H. W. (2003). Functional modules by relating protein interaction networks and gene expression. Nucleic Acids Res. 31, 6283-6289. doi: 10.1093/nar/gkg838
    • (2003) Nucleic Acids Res. , vol.31 , pp. 6283-6289
    • Tornow, S.1    Mewes, H.W.2
  • 62
    • 33846807390 scopus 로고    scopus 로고
    • Alternative routes and mutational robustness in complex regulatory networks
    • doi: 10.1016/j.biosystems.2006.06.002
    • Wagner, A., and Wright, J. (2007). Alternative routes and mutational robustness in complex regulatory networks. BioSystems 88, 163-172. doi: 10.1016/j.biosystems.2006.06.002
    • (2007) BioSystems , vol.88 , pp. 163-172
    • Wagner, A.1    Wright, J.2
  • 63
    • 84870311928 scopus 로고    scopus 로고
    • Quantitative modeling of transcriptional regulatory networks by integrating multiple source of knowledge
    • Wang, S. Q., and Li, H. X. (2012). Quantitative modeling of transcriptional regulatory networks by integrating multiple source of knowledge. Bioprocess Biosyst. Eng. 35, 1555-1565.
    • (2012) Bioprocess Biosyst. Eng. , vol.35 , pp. 1555-1565
    • Wang, S.Q.1    Li, H.X.2
  • 64
    • 10044280457 scopus 로고    scopus 로고
    • Learning module networks from genome-wide location and expression data
    • doi: 10.1016/j.febslet.2004.11.019
    • Xu, X., Wang, L., and Ding, D. (2004). Learning module networks from genome-wide location and expression data. FEBS Lett. 578, 297-304. doi: 10.1016/j.febslet.2004.11.019
    • (2004) FEBS Lett. , vol.578 , pp. 297-304
    • Xu, X.1    Wang, L.2    Ding, D.3
  • 65
    • 77955039075 scopus 로고    scopus 로고
    • Learning transcriptional networks from the integration of ChIP-chip and expression data in a non-parametric model
    • doi: 10.1093/bioinformatics/btq289
    • Youn, A., Reiss, D. J., and Stuetzle, W. (2010). Learning transcriptional networks from the integration of ChIP-chip and expression data in a non-parametric model. Bioinformatics 26, 1879-1886. doi: 10.1093/bioinformatics/btq289
    • (2010) Bioinformatics , vol.26 , pp. 1879-1886
    • Youn, A.1    Reiss, D.J.2    Stuetzle, W.3
  • 66
    • 33749514099 scopus 로고    scopus 로고
    • Genomic analysis of the hierarchical structure of regulatory networks
    • doi: 10.1073/pnas.0508637103
    • Yu, H., and Gerstein, M. (2006). Genomic analysis of the hierarchical structure of regulatory networks. Proc. Natl. Acad. Sci. U.S.A. 103, 14724-14731. doi: 10.1073/pnas.0508637103
    • (2006) Proc. Natl. Acad. Sci. U.S.A. , vol.103 , pp. 14724-14731
    • Yu, H.1    Gerstein, M.2
  • 67
    • 0042706147 scopus 로고    scopus 로고
    • Genomic analysis of gene expression relationships in transcriptional regulatory networks
    • doi: 10.1016/S0168-9525(03)00175-6
    • Yu, H., Luscombe, N. M., Qian, J., and Gerstein, M. (2003). Genomic analysis of gene expression relationships in transcriptional regulatory networks. Trends Genet. 19, 422-427. doi: 10.1016/S0168-9525(03)00175-6
    • (2003) Trends Genet. , vol.19 , pp. 422-427
    • Yu, H.1    Luscombe, N.M.2    Qian, J.3    Gerstein, M.4
  • 68
    • 27744472292 scopus 로고    scopus 로고
    • Inference of transcriptional regulatory network by two-stage constrained space factor analysis
    • doi: 10.1093/bioinformatics/bti656
    • Yu, T., and Li, K. C. (2005). Inference of transcriptional regulatory network by two-stage constrained space factor analysis. Bioinformatics 21, 4033-4038. doi: 10.1093/bioinformatics/bti656
    • (2005) Bioinformatics , vol.21 , pp. 4033-4038
    • Yu, T.1    Li, K.C.2
  • 69
    • 35548939345 scopus 로고    scopus 로고
    • Modular co-evolution of metabolic networks
    • doi: 10.1186/1471-2105-8-311
    • Zhao, J., Ding, G.-H., Tao, L., Yu, H., Yu, Z.-H., Luo, J.-H., et al. (2007). Modular co-evolution of metabolic networks. BMC Bioinformatics 8, 311. doi: 10.1186/1471-2105-8-311
    • (2007) BMC Bioinformatics , vol.8 , pp. 311
    • Zhao, J.1    Ding, G.-H.2    Tao, L.3    Yu, H.4    Yu, Z.-H.5    Luo, J.-H.6


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