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Volumn 3 JUN, Issue , 2012, Pages

Mathematical and statistical modeling in cancer systems biology

Author keywords

Cancer; Dynamic; Graphical models; High throughput data; Metabolism; Odes; Steady state

Indexed keywords


EID: 84866343535     PISSN: None     EISSN: 1664042X     Source Type: Journal    
DOI: 10.3389/fphys.2012.00227     Document Type: Review
Times cited : (26)

References (91)
  • 1
    • 77956498018 scopus 로고    scopus 로고
    • Sloppy models, parameter uncertainty, and the role of experimental design
    • Apgar, J. F., Witmer, D. K., White, F. M., and Tidor, B. (2010). Sloppy models, parameter uncertainty, and the role of experimental design. Mol Biosyst. 6, 1890-1900.
    • (2010) Mol Biosyst , vol.6 , pp. 1890-1900
    • Apgar, J.F.1    Witmer, D.K.2    White, F.M.3    Tidor, B.4
  • 3
    • 33747884345 scopus 로고    scopus 로고
    • Gene expression omnibus: microarray data storage, submission, retrieval, and analysis
    • Barrett, T., and Edgar, R. (2006). Gene expression omnibus: microarray data storage, submission, retrieval, and analysis. Meth. Enzymol. 411, 352-369.
    • (2006) Meth. Enzymol. , vol.411 , pp. 352-369
    • Barrett, T.1    Edgar, R.2
  • 5
    • 0036139520 scopus 로고    scopus 로고
    • Progenetix. net: an online repository for molecular cytogenetic aberration data
    • Baudis, M., and Cleary, M. (2001). Progenetix. net: an online repository for molecular cytogenetic aberration data. Bioinformatics 17, 1228-1229.
    • (2001) Bioinformatics , vol.17 , pp. 1228-1229
    • Baudis, M.1    Cleary, M.2
  • 8
    • 33749014147 scopus 로고    scopus 로고
    • Large-scale Bayesian parameter estimation for a three-compartment cardiac metabolism model during ischemia
    • Calvetti, D., Hageman, R., and Somer-salo, E. (2006). Large-scale Bayesian parameter estimation for a three-compartment cardiac metabolism model during ischemia. Inverse Probl. 22, 1797-1816.
    • (2006) Inverse Probl , vol.22 , pp. 1797-1816
    • Calvetti, D.1    Hageman, R.2    Somer-Salo, E.3
  • 9
    • 34249661485 scopus 로고    scopus 로고
    • Large-scale statistical parameter estimation in complex systems with an application to metabolic models
    • Calvetti, D., and Somersalo, E. (2006). Large-scale statistical parameter estimation in complex systems with an application to metabolic models. Multiscale Model. Simul. 5,1333.
    • (2006) Multiscale Model. Simul. , vol.5 , pp. 1333
    • Calvetti, D.1    Somersalo, E.2
  • 10
    • 62549125109 scopus 로고    scopus 로고
    • High-dimensional sparse factor modeling: applications in gene expression genomics
    • Carvalho, C., Chang, J., Lucas, J., Nevins, J., Wang, Q., and West, M. (2008). High-dimensional sparse factor modeling: applications in gene expression genomics. J. Am. Stat. Assoc. 103, 1438-1456.
    • (2008) J. Am. Stat. Assoc. , vol.103 , pp. 1438-1456
    • Carvalho, C.1    Chang, J.2    Lucas, J.3    Nevins, J.4    Wang, Q.5    West, M.6
  • 11
    • 43249116959 scopus 로고    scopus 로고
    • Understanding nf-κb signaling via mathematical modeling
    • Cheong, R., Hoffmann, A., and Levchenko, A. (2008). Understanding nf-κb signaling via mathematical modeling. Mol. Syst. Biol. 4, 192.
    • (2008) Mol. Syst. Biol. , vol.4 , pp. 192
    • Cheong, R.1    Hoffmann, A.2    Levchenko, A.3
  • 13
    • 84866347332 scopus 로고    scopus 로고
    • Mapping the cancer genome
    • Collins, F., and Barker, A. (2008). Mapping the cancer genome. Spec. Ed. 18, 22-29.
    • (2008) Spec. Ed. , vol.18 , pp. 22-29
    • Collins, F.1    Barker, A.2
  • 14
    • 24944586285 scopus 로고    scopus 로고
    • Achieving stability of lipopolysaccharide-induced nf-κb activation
    • Covert, M., Leung, T., Gaston, J., and Baltimore, D. (2005). Achieving stability of lipopolysaccharide-induced nf-κb activation. Science 309,1854.
    • (2005) Science , vol.309 , pp. 1854
    • Covert, M.1    Leung, T.2    Gaston, J.3    Baltimore, D.4
  • 18
    • 76949106424 scopus 로고    scopus 로고
    • Selecting high-dimensional mixed graphical models using minimal aic or bic forests
    • Edwards, D., De Abreu, G., and Labouriau, R. (2010). Selecting high-dimensional mixed graphical models using minimal aic or bic forests. BMC Bioinformatics 11, 18. doi:10.1186/1471-2105-11-18
    • (2010) BMC Bioinformatics , vol.11 , pp. 18
    • Edwards, D.1    De Abreu, G.2    Labouriau, R.3
  • 19
    • 2942579562 scopus 로고    scopus 로고
    • Metabolic flux balance analysis and the in silico analysis of Escherichia coli k-12 gene deletions
    • Edwards, J., and Palsson, B. (2000). Metabolic flux balance analysis and the in silico analysis of Escherichia coli k-12 gene deletions. BMC Bioinformatics 1, 1. doi:10.1186/1471-2105-1-1
    • (2000) BMC Bioinformatics , vol.1 , pp. 1
    • Edwards, J.1    Palsson, B.2
  • 20
    • 79954550872 scopus 로고    scopus 로고
    • Practical limits for reverse engineering of dynamical systems: a statistical analysis of sensitivity and parameter inferability in systems biology models
    • Erguler, K., and Stumpf, M. P. H. (2011). Practical limits for reverse engineering of dynamical systems: a statistical analysis of sensitivity and parameter inferability in systems biology models. Mol. Biosyst. 7, 1593-1602.
    • (2011) Mol. Biosyst. , vol.7 , pp. 1593-1602
    • Erguler, K.1    Stumpf, M.P.H.2
  • 23
    • 0037313750 scopus 로고    scopus 로고
    • Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network
    • Förster, J., Famili, I., Fu, P., Palsson, B., and Nielsen, J. (2003). Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res. 13, 244-253.
    • (2003) Genome Res , vol.13 , pp. 244-253
    • Förster, J.1    Famili, I.2    Fu, P.3    Palsson, B.4    Nielsen, J.5
  • 24
    • 35348819870 scopus 로고    scopus 로고
    • Mathematical analysis and challenges arising from models of tumor growth
    • Friedman, A., Bellomo, N., and Maini, P. (2007). Mathematical analysis and challenges arising from models of tumor growth. Math. Models Meth-odsAppl. Sci. 17, 1751-1772.
    • (2007) Math. Models MethodsAppl. Sci. , vol.17 , pp. 1751-1772
    • Friedman, A.1    Bellomo, N.2    Maini, P.3
  • 25
    • 45849134070 scopus 로고    scopus 로고
    • Sparse inverse covariance estimation with the graphical lasso
    • Friedman, J., Hastie, T., and Tibshirani, R. (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics 9, 432-441.
    • (2008) Biostatistics , vol.9 , pp. 432-441
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 26
    • 0033636139 scopus 로고    scopus 로고
    • Support vector machine classification and validation of cancer tissue samples using microarray expression data
    • Furey, T., Cristianini, N., Duffy, N., Bednarski, D., Schummer, M., and Haussler, D. (2000). Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics 16,906-914.
    • (2000) Bioinformatics , vol.16 , pp. 906-914
    • Furey, T.1    Cristianini, N.2    Duffy, N.3    Bednarski, D.4    Schummer, M.5    Haussler, D.6
  • 28
    • 0020963903 scopus 로고
    • Physiologically based pharmacokinetic modeling: principles and applications
    • Gerlowski, L., and Jain, R. (1983). Physiologically based pharmacokinetic modeling: principles and applications. J. Pharm. Sci. 72, 1103-1127.
    • (1983) J. Pharm. Sci. , vol.72 , pp. 1103-1127
    • Gerlowski, L.1    Jain, R.2
  • 29
    • 70350672603 scopus 로고    scopus 로고
    • Quantifying cancer progression with conjunctive Bayesian networks
    • Gerstung, M., Baudis, M., Moch, H., and Beerenwinkel, N. (2009). Quantifying cancer progression with conjunctive Bayesian networks. Bioinformatics 25,2809-2815.
    • (2009) Bioinformatics , vol.25 , pp. 2809-2815
    • Gerstung, M.1    Baudis, M.2    Moch, H.3    Beerenwinkel, N.4
  • 30
    • 33747891871 scopus 로고    scopus 로고
    • Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks
    • Gevaert, O., De Smet, F., Timmerman, D., Moreau, Y., and De Moor, B. (2006). Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks. Bioinformatics 22, e184- e190.
    • (2006) Bioinformatics , vol.22
    • Gevaert, O.1    De Smet, F.2    Timmerman, D.3    Moreau, Y.4    De Moor, B.5
  • 32
    • 78249277673 scopus 로고
    • Nitrogen mustard therapy; use of methyl-bis (beta-chloroethyl) amine hydrochloride and tris (beta-chloroethyl) amine hydrochloride for hodgkin's disease, lymphosar-coma, leukemia and certain allied and miscellaneous disorders
    • Goodman, L., Wintrobe, M., Dameshek, W., Goodman, M., Gilman, A., and McLennan, M. (1946). Nitrogen mustard therapy; use of methyl-bis (beta-chloroethyl) amine hydrochloride and tris (beta-chloroethyl) amine hydrochloride for hodgkin's disease, lymphosar-coma, leukemia and certain allied and miscellaneous disorders. J. Am. Med. Assoc. 132,125-132.
    • (1946) J. Am. Med. Assoc. , vol.132 , pp. 125-132
    • Goodman, L.1    Wintrobe, M.2    Dameshek, W.3    Goodman, M.4    Gilman, A.5    McLennan, M.6
  • 34
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • Guyon, I., Weston, J., Barnhill, S., and Vapnik, V. (2002). Gene selection for cancer classification using support vector machines. Mach. Learn. 46, 389-422.
    • (2002) Mach. Learn. , vol.46 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 35
    • 79955455061 scopus 로고    scopus 로고
    • A Bayesian framework for inference of the genotype-phenotype map for segregating populations
    • Hageman, R. S., Leduc, M. S., Korstanje, R., Paigen, B., and Churchill, G. A. (2011). A Bayesian framework for inference of the genotype-phenotype map for segregating populations. Genetics 187, 1163-1170.
    • (2011) Genetics , vol.187 , pp. 1163-1170
    • Hageman, R.S.1    Leduc, M.S.2    Korstanje, R.3    Paigen, B.4    Churchill, G.A.5
  • 36
    • 80052242132 scopus 로고    scopus 로고
    • Targeting cancer metabolism: a therapeutic window opens
    • Heiden, M. V. (2011). Targeting cancer metabolism: a therapeutic window opens. Nat. Rev. Drug Discov. 10, 671-684.
    • (2011) Nat. Rev. Drug Discov. , vol.10 , pp. 671-684
    • Heiden, M.V.1
  • 37
    • 0037044575 scopus 로고    scopus 로고
    • The iκb-nf-κb signaling module: temporal control and selective gene activation
    • Hoffmann, A., Levchenko, A., Scott, M., and Baltimore, D. (2002). The iκb-nf-κb signaling module: temporal control and selective gene activation. Science 298, 1241.
    • (2002) Science , vol.298 , pp. 1241
    • Hoffmann, A.1    Levchenko, A.2    Scott, M.3    Baltimore, D.4
  • 39
    • 3242875300 scopus 로고    scopus 로고
    • Combining microarrays and biological knowledge for estimating gene networks via Bayesian networks
    • 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.
    • (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
  • 41
    • 0037169358 scopus 로고    scopus 로고
    • Apoptosis:: a link between cancer genetics and chemotherapy
    • Johnstone, R., Ruefli, A., and Lowe, S. (2002). Apoptosis:: a link between cancer genetics and chemotherapy. Cell 108, 153-164.
    • (2002) Cell , vol.108 , pp. 153-164
    • Johnstone, R.1    Ruefli, A.2    Lowe, S.3
  • 43
    • 0035357333 scopus 로고    scopus 로고
    • A Bayesian network for diagnosis of primary bone tumors
    • Kahn, C., Laur, J., and Carrera, G. (2001). A Bayesian network for diagnosis of primary bone tumors. J. Digit. Imaging 14, 56-57.
    • (2001) J. Digit. Imaging , vol.14 , pp. 56-57
    • Kahn, C.1    Laur, J.2    Carrera, G.3
  • 44
    • 0037079054 scopus 로고    scopus 로고
    • Computational systems biology
    • Kitano, H. (2002). Computational systems biology. Nature 420, 206-210.
    • (2002) Nature , vol.420 , pp. 206-210
    • Kitano, H.1
  • 46
    • 0038047901 scopus 로고    scopus 로고
    • On learning gene regulatory networks under the Boolean network model
    • Lähdesmäki, H., Shmulevich, I., and Yli-Harja, O. (2003). On learning gene regulatory networks under the Boolean network model. Mach. Learn. 52, 147-167.
    • (2003) Mach. Learn. , vol.52 , pp. 147-167
    • Lähdesmäki, H.1    Shmulevich, I.2    Yli-Harja, O.3
  • 47
    • 60549111634 scopus 로고    scopus 로고
    • Wgcna: an r package for weighted correlation network analysis
    • Langfelder, P., and Horvath, S. (2008). Wgcna: an r package for weighted correlation network analysis. BMC Bioinformatics 9, 559. doi:10.1186/1471-2105-9-559
    • (2008) BMC Bioinformatics , vol.9 , pp. 559
    • Langfelder, P.1    Horvath, S.2
  • 48
    • 33748464202 scopus 로고    scopus 로고
    • Flux balance analysis in the era of metabolomics
    • Lee, J., Gianchandani, E., and Papin, J. (2006). Flux balance analysis in the era of metabolomics. Brief. Bioinformatics 7, 140-150.
    • (2006) Brief. Bioinformatics , vol.7 , pp. 140-150
    • Lee, J.1    Gianchandani, E.2    Papin, J.3
  • 49
    • 78549270383 scopus 로고    scopus 로고
    • Critical reasoning on causal inference in genome-wide linkage and association studies
    • Li, Y., Tesson, B.M., Churchill, G. A., and Jansen, R. C. (2010). Critical reasoning on causal inference in genome-wide linkage and association studies. Trends Genet. 26, 493-498.
    • (2010) Trends Genet , vol.26 , pp. 493-498
    • Li, Y.1    Tesson, B.M.2    Churchill, G.A.3    Jansen, R.C.4
  • 50
    • 77956417789 scopus 로고    scopus 로고
    • Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism
    • Livnat Jerby, T., and Ruppin, E. (2010). Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism. Mol. Syst. Biol. 6, 401.
    • (2010) Mol. Syst. Biol. , vol.6 , pp. 401
    • Livnat Jerby, T.1    Ruppin, E.2
  • 51
    • 77950650137 scopus 로고    scopus 로고
    • Biology-driven cancer drug development
    • Lord, C., and Ashworth, A. (2010). Biology-driven cancer drug development. BMC Biol. 8, 38. doi:10.1186/1741-7007-8-38
    • (2010) BMC Biol , vol.8 , pp. 38
    • Lord, C.1    Ashworth, A.2
  • 52
    • 77956516647 scopus 로고    scopus 로고
    • Cancer metabolism: is glu-tamine sweeter than glucose?
    • Lu, W., Pelicano, H., and Huang, P. (2010). Cancer metabolism: is glu-tamine sweeter than glucose? Cancer Cell 18, 199-200.
    • (2010) Cancer Cell , vol.18 , pp. 199-200
    • Lu, W.1    Pelicano, H.2    Huang, P.3
  • 53
    • 38449118125 scopus 로고    scopus 로고
    • A comparison of non-standard solvers for odes describing cellular reactions in the heart
    • MacLachlan, M., Sundnes, J., and Spi-teri,R. (2007). A comparison of non-standard solvers for odes describing cellular reactions in the heart. Comput. Methods Biomech. Biomed. Engin. 10,317-326.
    • (2007) Comput. Methods Biomech. Biomed. Engin. , vol.10 , pp. 317-326
    • MacLachlan, M.1    Sundnes, J.2    Spi-teri, R.3
  • 54
    • 0141680424 scopus 로고    scopus 로고
    • Cell signaling and cancer
    • Martin, G. (2003). Cell signaling and cancer. Cancer Cell 4,167-174.
    • (2003) Cancer Cell , vol.4 , pp. 167-174
    • Martin, G.1
  • 56
    • 0012249041 scopus 로고
    • Metabolism of neoplastic tissue. IV. A study of lipid synthesis in neoplastic tissue slices in vitro
    • Medes, G., Thomas, A., and Weinhouse, S. (1953). Metabolism of neoplastic tissue. IV. A study of lipid synthesis in neoplastic tissue slices in vitro. Cancer Res. 13,27.
    • (1953) Cancer Res , vol.13 , pp. 27
    • Medes, G.1    Thomas, A.2    Weinhouse, S.3
  • 57
    • 77950943011 scopus 로고    scopus 로고
    • Logic-based models for the analysis of cell signaling networks
    • Morris, M., Saez-Rodriguez, J., Sorger, P., and Lauffenburger, D. (2010). Logic-based models for the analysis of cell signaling networks. Biochemistry 49,3216-3224.
    • (2010) Biochemistry , vol.49 , pp. 3216-3224
    • Morris, M.1    Saez-Rodriguez, J.2    Sorger, P.3    Lauffenburger, D.4
  • 58
    • 55749093996 scopus 로고    scopus 로고
    • Network inference using informative priors
    • Mukherjee, S., and Speed, T. (2008). Network inference using informative priors. Proc. Natl. Acad. Sci. U.S.A. 105, 14313.
    • (2008) Proc. Natl. Acad. Sci. U.S.A. , vol.105 , pp. 14313
    • Mukherjee, S.1    Speed, T.2
  • 59
    • 84870284276 scopus 로고    scopus 로고
    • Causal graphical models in systems genetics: a unified framework for joint inference of causal network and genetic architecture for correlated phenotypes
    • Neto, E., Keller, M., Attie, A., and Yandell, B. (2010). Causal graphical models in systems genetics: a unified framework for joint inference of causal network and genetic architecture for correlated phenotypes. Ann. Appl Stat. 4, 320-339.
    • (2010) Ann. Appl Stat. , vol.4 , pp. 320-339
    • Neto, E.1    Keller, M.2    Attie, A.3    Yandell, B.4
  • 61
    • 73149122136 scopus 로고    scopus 로고
    • Applications of genome-scale metabolic reconstructions
    • Oberhardt, M., Palsson, B., and Papin, J. (2009). Applications of genome-scale metabolic reconstructions. Mol. Syst. Biol. 5, 320.
    • (2009) Mol. Syst. Biol. , vol.5 , pp. 320
    • Oberhardt, M.1    Palsson, B.2    Papin, J.3
  • 63
    • 0021466891 scopus 로고
    • Liver and adipose tissue contributions to newly formed fatty acids in an ascites tumor
    • Ookhtens, M., Kannan, R., Lyon, I., and Baker, N. (1984). Liver and adipose tissue contributions to newly formed fatty acids in an ascites tumor. Am. J. Physiol. 247, R146-R153.
    • (1984) Am. J. Physiol. , vol.247
    • Ookhtens, M.1    Kannan, R.2    Lyon, I.3    Baker, N.4
  • 64
    • 29144435996 scopus 로고    scopus 로고
    • Computational modelling of the receptor-tyrosine-kinase-activated mapk pathway
    • Orton, R., Sturm, O., Vyshemirsky, V., Calder, M., Gilbert, D., and Kolch, W. (2005). Computational modelling of the receptor-tyrosine-kinase-activated mapk pathway. Biochem. J. 392(Pt2), 249.
    • (2005) Biochem. J. , vol.392 , Issue.PART 2 , pp. 249
    • Orton, R.1    Sturm, O.2    Vyshemirsky, V.3    Calder, M.4    Gilbert, D.5    Kolch, W.6
  • 66
    • 84859746988 scopus 로고    scopus 로고
    • Enhancing apoptosis in trail-resistant cancer cells using fundamental response rules
    • Piras, V., Hayashi, K., Tomita, M., and Selvarajoo, K. (2011). Enhancing apoptosis in trail-resistant cancer cells using fundamental response rules. Sci. Rep. 1, 144.
    • (2011) Sci. Rep. , vol.1 , pp. 144
    • Piras, V.1    Hayashi, K.2    Tomita, M.3    Selvarajoo, K.4
  • 67
    • 78651453837 scopus 로고    scopus 로고
    • Network analysis of skin tumor progression identifies a rewired genetic architecture affecting inflammation and tumor susceptibility
    • Quigley, D., To, M., Jin Kim, I., Lin, K., Albertson, D., Sjolund, J., Perez-Losada, J., and Balmain, A. (2011). Network analysis of skin tumor progression identifies a rewired genetic architecture affecting inflammation and tumor susceptibility. Genome Biol. 12, R5.
    • (2011) Genome Biol , vol.12
    • Quigley, D.1    To, M.2    Jin Kim, I.3    Lin, K.4    Albertson, D.5    Sjolund, J.6    Perez-Losada, J.7    Balmain, A.8
  • 68
    • 0025133542 scopus 로고
    • Estimating the risk of liver cancer associated with human exposures to chloroform using physiologically based pharmacokinetic modeling
    • Reitz, R., Mendrala, A., Corley, R., Quast, J., Gargas, M., Andersen, M., Staats, D., and Conolly, R. (1990). Estimating the risk of liver cancer associated with human exposures to chloroform using physiologically based pharmacokinetic modeling. Toxicol. Appl. Pharmacol. 105, 443-459.
    • (1990) Toxicol. Appl. Pharmacol. , vol.105 , pp. 443-459
    • Reitz, R.1    Mendrala, A.2    Corley, R.3    Quast, J.4    Gargas, M.5    Andersen, M.6    Staats, D.7    Conolly, R.8
  • 69
    • 62549151382 scopus 로고    scopus 로고
    • Effects of genetic and environmental factors on trait network predictions from quantitative trait locus data
    • Remington, D. L. (2009). Effects of genetic and environmental factors on trait network predictions from quantitative trait locus data. Genetics 181,1087-1099.
    • (2009) Genetics , vol.181 , pp. 1087-1099
    • Remington, D.L.1
  • 70
    • 33751226638 scopus 로고    scopus 로고
    • A multiscale mathematical model of avascular tumor growth to investigate the therapeutic benefit of anti-invasive agents
    • Ribba, B., Saut, O., Colin, T., Bresch, D., Grenier, E., and Boissel, J. (2006). A multiscale mathematical model of avascular tumor growth to investigate the therapeutic benefit of anti-invasive agents. J. Theor. Biol. 243, 532-541.
    • (2006) J. Theor. Biol. , vol.243 , pp. 532-541
    • Ribba, B.1    Saut, O.2    Colin, T.3    Bresch, D.4    Grenier, E.5    Boissel, J.6
  • 72
    • 57649124192 scopus 로고    scopus 로고
    • Reverse engineering the genotype-phenotype map with natural genetic variation
    • Rockman, M. (2008). Reverse engineering the genotype-phenotype map with natural genetic variation. Nature 456, 738-744.
    • (2008) Nature , vol.456 , pp. 738-744
    • Rockman, M.1
  • 74
    • 20044388557 scopus 로고    scopus 로고
    • From signatures to models: understanding cancer using microarrays
    • Segal, E., Friedman, N., Kaminski, N., Regev, A., and Koller, D. (2005). From signatures to models: understanding cancer using microarrays. Nat. Genet. 37, S38-S45.
    • (2005) Nat. Genet. , vol.37
    • Segal, E.1    Friedman, N.2    Kaminski, N.3    Regev, A.4    Koller, D.5
  • 75
    • 79954591119 scopus 로고    scopus 로고
    • Macroscopic law of conservation revealed in the population dynamics of toll-like receptor signaling
    • Selvarajoo, K. (2011). Macroscopic law of conservation revealed in the population dynamics of toll-like receptor signaling. Cell Commun. Signal 9,9.
    • (2011) Cell Commun. Signal , vol.9 , pp. 9
    • Selvarajoo, K.1
  • 76
    • 72949118860 scopus 로고    scopus 로고
    • Genome-scale modeling and in silico analysis of mouse cell metabolic network
    • Selvarasu, S., Karimi, I., Ghim, G., and Lee, D. (2010). Genome-scale modeling and in silico analysis of mouse cell metabolic network. Mol. Biosyst. 6, 151-161.
    • (2010) Mol. Biosyst. , vol.6 , pp. 151-161
    • Selvarasu, S.1    Karimi, I.2    Ghim, G.3    Lee, D.4
  • 78
    • 79953661070 scopus 로고    scopus 로고
    • Genome-scale metabolic modeling elucidates the role of proliferative adaptation in causing the warburg effect
    • Shlomi, T., Benyamini, T., Gottlieb, E., Sharan, R., and Ruppin, E. (2011). Genome-scale metabolic modeling elucidates the role of proliferative adaptation in causing the warburg effect. PLoS Comput. Biol. 7, 151-161. doi:10.1371/journal.pcbi.1002018
    • (2011) PLoS Comput. Biol. , vol.7 , pp. 151-161
    • Shlomi, T.1    Benyamini, T.2    Gottlieb, E.3    Sharan, R.4    Ruppin, E.5
  • 79
    • 80051580618 scopus 로고    scopus 로고
    • The impact of eliminating socioeconomic and racial disparities on premature cancer deaths
    • Siegel, R., Ward, E., Brawley, O., and Jemal, A. (2011). The impact of eliminating socioeconomic and racial disparities on premature cancer deaths. CA Cancer J. Clin. 61, 212-236.
    • (2011) CA Cancer J. Clin. , vol.61 , pp. 212-236
    • Siegel, R.1    Ward, E.2    Brawley, O.3    Jemal, A.4
  • 80
    • 0035307231 scopus 로고    scopus 로고
    • Partial differential equations of chemo-taxis and angiogenesis
    • Sleeman, B., and Levine, H. (2001). Partial differential equations of chemo-taxis and angiogenesis. Math. Methods Appl. Sci. 24, 405-426.
    • (2001) Math. Methods Appl. Sci. , vol.24 , pp. 405-426
    • Sleeman, B.1    Levine, H.2
  • 82
    • 77952781776 scopus 로고    scopus 로고
    • Data integration for dynamic and sustainable systems biology resources: challenges and lessons learned
    • Sullivan, D., Gabbard, J. Jr., Shukla, M., and Sobral, B. (2010). Data integration for dynamic and sustainable systems biology resources: challenges and lessons learned. Chem. Biodivers. 7, 1124-1141.
    • (2010) Chem. Biodivers. , vol.7 , pp. 1124-1141
    • Sullivan, D.1    Gabbard Jr., J.2    Shukla, M.3    Sobral, B.4
  • 83
    • 84860390334 scopus 로고    scopus 로고
    • Predictive biomarkers: a paradigm shift towards personalized cancer medicine
    • Thangue, N. L., and Kerr, D. (2011). Predictive biomarkers: a paradigm shift towards personalized cancer medicine. Nat. Rev. Clin. Oncol. 8, 587-596.
    • (2011) Nat. Rev. Clin. Oncol. , vol.8 , pp. 587-596
    • Thangue, N.L.1    Kerr, D.2
  • 85
    • 84856151338 scopus 로고    scopus 로고
    • Science funding: provocative questions in cancer research
    • Varmus, H., and Harlow, E. (2012). Science funding: provocative questions in cancer research. Nature 481, 436-437.
    • (2012) Nature , vol.481 , pp. 436-437
    • Varmus, H.1    Harlow, E.2
  • 87
    • 12444279265 scopus 로고
    • On the origin of cancer cells
    • Warburg, O. (1956). On the origin of cancer cells. Science 123, 309-314.
    • (1956) Science , vol.123 , pp. 309-314
    • Warburg, O.1
  • 88
    • 34249774309 scopus 로고    scopus 로고
    • Reconstructing gene regulatory networks with Bayesian networks by combining expression data with multiple sources of prior knowledge
    • Werhli, A.V., and Husmeier, D. (2007). Reconstructing gene regulatory networks with Bayesian networks by combining expression data with multiple sources of prior knowledge. Stat. Appl. Genet. Mol. Biol. 6, 15.
    • (2007) Stat. Appl. Genet. Mol. Biol. , vol.6 , pp. 15
    • Werhli, A.V.1    Husmeier, D.2
  • 89
    • 24944489952 scopus 로고    scopus 로고
    • Stimulus specificity of gene expression programs determined by temporal control of IKK activity
    • Werner, S., Barken, D., and Hoffmann, A. (2005). Stimulus specificity of gene expression programs determined by temporal control of IKK activity. Science 309, 1857.
    • (2005) Science , vol.309 , pp. 1857
    • Werner, S.1    Barken, D.2    Hoffmann, A.3
  • 90
    • 77953553836 scopus 로고    scopus 로고
    • Bayesian learning in sparse graphical factor models via variational mean-field annealing
    • Yoshida, R., and West, M. (2010). Bayesian learning in sparse graphical factor models via variational mean-field annealing. J. Mach. Learn. Res. 11, 1771-1798.
    • (2010) J. Mach. Learn. Res. , vol.11 , pp. 1771-1798
    • Yoshida, R.1    West, M.2
  • 91
    • 44649195625 scopus 로고    scopus 로고
    • Targeted therapy in the treatment of solid tumors: practice contradicts theory
    • Zhukov, N., and Tjulandin, S. (2007). Targeted therapy in the treatment of solid tumors: practice contradicts theory. Biochemistry 73, 605-618.
    • (2007) Biochemistry , vol.73 , pp. 605-618
    • Zhukov, N.1    Tjulandin, S.2


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