×

zbMATH — the first resource for mathematics

Systems biology: the next frontier for bioinformatics. (English) Zbl 1219.92023
Summary: Biochemical systems biology augments more traditional disciplines, such as genomics, biochemistry and molecular biology, by championing (i) mathematical and computational modeling; (ii) the application of traditional engineering practices in the analysis of biochemical systems; and in the past decade increasingly (iii) the use of near-comprehensive data sets derived from ‘omics platform technologies, in particular ‘downstream’ technologies relative to genome sequencing, including transcriptomics, proteomics and metabolomics. The future progress in understanding biological principles will increasingly depend on the development of temporal and spatial analytical techniques that will provide high-resolution data for systems analyses. To date, particularly successful were strategies involving (a) quantitative measurements of cellular components at the mRNA, protein and metabolite levels, as well as in vivo metabolic reaction rates, (b) development of mathematical models that integrate biochemical knowledge with the information generated by high-throughput experiments, and (c) applications to microbial organisms. The inevitable role bioinformatics plays in modern systems biology puts mathematical and computational sciences as an equal partner to analytical and experimental biology. Furthermore, mathematical and computational models are expected to become increasingly prevalent representations of our knowledge about specific biochemical systems.
MSC:
92C40 Biochemistry, molecular biology
92C42 Systems biology, networks
PDF BibTeX XML Cite
Full Text: DOI
References:
[1] T. Ideker, T. Galitski, and L. Hood, “A new approach to decoding life: systems biology,” Annual Review of Genomics and Human Genetics, vol. 2, pp. 343-372, 2001. · doi:10.1146/annurev.genom.2.1.343
[2] H. Kitano, “Computational systems biology,” Nature, vol. 420, no. 6912, pp. 206-210, 2002. · doi:10.1038/nature01254
[3] H. Kitano, “Systems biology: a brief overview,” Science, vol. 295, no. 5560, pp. 1662-1664, 2002. · doi:10.1126/science.1069492
[4] H. V. Westerhoff and B. O. Palsson, “The evolution of molecular biology into systems biology,” Nature Biotechnology, vol. 22, no. 10, pp. 1249-1252, 2004. · doi:10.1038/nbt1020
[5] J. Stelling, “Mathematical models in microbial systems biology,” Current Opinion in Microbiology, vol. 7, no. 5, pp. 513-518, 2004. · doi:10.1016/j.mib.2004.08.004
[6] E. S. Lander, L. M. Linton, B. Birren, et al., “Initial sequencing and analysis of the human genome,” Nature, vol. 409, pp. 860-921, 2001.
[7] J. Craig Venter, M. D. Adams, E. W. Myers et al., “The sequence of the human genome,” Science, vol. 291, no. 5507, pp. 1304-1351, 2001. · doi:10.1126/science.1058040
[8] M. Schena, D. Shalon, R. W. Davis, and P. O. Brown, “Quantitative monitoring of gene expression patterns with a complementary DNA microarray,” Science, vol. 270, no. 5235, pp. 467-470, 1995.
[9] D. A. Lashkari, J. L. DeRisi, J. H. Mccusker et al., “Yeast microarrays for genome wide parallel genetic and gene expression analysis,” Proceedings of the National Academy of Sciences of the United States of America, vol. 94, no. 24, pp. 13057-13062, 1997. · doi:10.1073/pnas.94.24.13057
[10] S. D. Patterson and R. H. Aebersold, “Proteomics: the first decade and beyond,” Nature Genetics, vol. 33, pp. 311-323, 2003. · doi:10.1038/ng1106
[11] S. G. Oliver, M. K. Winson, D. B. Kell, and F. Baganz, “Systematic functional analysis of the yeast genome,” Trends in Biotechnology, vol. 16, no. 9, pp. 373-378, 1998. · doi:10.1016/S0167-7799(98)01214-1
[12] O. Fiehn, “Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks,” Comparative and Functional Genomics, vol. 2, no. 3, pp. 155-168, 2001. · doi:10.1002/cfg.82
[13] N. Wiener, Cybernetics: Or Control and Communication in the Animan and the Machine, MIT Press, Cambridge, Mass, USA, 1946.
[14] M. D. Mesarovic, “Systems theory and biology-view of a theoretician,” in Systems Theory and Biology, M. D. Mesarovic, Ed., pp. 59-87, Springer, New York, NY, USA, 1968.
[15] L. von Bertalanffy, General System Theory, George Braziller, New York, NY, USA, 1969.
[16] H. Kacser and J. A. Burns, “The control of flux,” Symposia of the Society for Experimental Biology, vol. 27, pp. 65-104, 1973.
[17] R. Heinrich and T. A. Rapoport, “A linear steady state treatment of enzymatic chains: general properties, control and effector strength,” European Journal of Biochemistry, vol. 42, no. 1, pp. 89-95, 1974.
[18] H. Kacser and J. A. Burns, “The molecular basis of dominance,” Genetics, vol. 97, no. 3-4, pp. 639-666, 1981.
[19] O. Wolkenhauer, “Systems biology: the reincarnation of systems theory applied in biology?” Briefings in Bioinformatics, vol. 2, no. 3, pp. 258-270, 2001.
[20] S. A. Benner and A. M. Sismour, “Synthetic biology,” Nature Reviews Genetics, vol. 6, no. 7, pp. 533-543, 2005. · doi:10.1038/nrg1637
[21] R. McDaniel and R. Weiss, “Advances in synthetic biology: on the path from prototypes to applications,” Current Opinion in Biotechnology, vol. 16, no. 4, pp. 476-483, 2005. · doi:10.1016/j.copbio.2005.07.002
[22] M. Heinemann and S. Panke, “Synthetic biology-putting engineering into biology,” Bioinformatics, vol. 22, no. 22, pp. 2790-2799, 2006. · doi:10.1093/bioinformatics/btl469
[23] C. L. Barrett, T. Y. Kim, H. U. Kim, B. Ø. Palsson, and S. Y. Lee, “Systems biology as a foundation for genome-scale synthetic biology,” Current Opinion in Biotechnology, vol. 17, no. 5, pp. 488-492, 2006. · doi:10.1016/j.copbio.2006.08.001
[24] S. Mukherji and A. van Oudenaarden, “Synthetic biology: understanding biological design from synthetic circuits,” Nature Reviews Genetics, vol. 10, no. 12, pp. 859-871, 2009. · doi:10.1038/nrg2697
[25] J. M. Vieites, M.-E. Guazzaroni, A. Beloqui, P. N. Golyshin, and M. Ferrer, “Metagenomics approaches in systems microbiology,” FEMS Microbiology Reviews, vol. 33, no. 1, pp. 236-255, 2009. · doi:10.1111/j.1574-6976.2008.00152.x
[26] E. T. Liu, “Systems biology, integrative biology, predictive biology,” Cell, vol. 121, no. 4, pp. 505-506, 2005. · doi:10.1016/j.cell.2005.04.021
[27] P. M. O’Callaghan and D. C. James, “Systems biotechnology of mammalian cell factories,” Briefings in Functional Genomics and Proteomics, vol. 7, no. 2, pp. 95-110, 2008. · doi:10.1093/bfgp/eln012
[28] S. A. Tomlins, M. A. Rubin, and A. M. Chinnaiyan, “Integrative biology of prostate cancer progression,” Annual Review of Pathology, vol. 1, pp. 243-271, 2006. · doi:10.1146/annurev.pathol.1.110304.100047
[29] E. T. Liu, “Integrative biology-a strategy for systems biomedicine,” Nature Reviews Genetics, vol. 10, no. 1, pp. 64-68, 2009. · doi:10.1038/nrg2488
[30] C. S. Riesenfeld, P. D. Schloss, and J. Handelsman, “Metagenomics: genomic analysis of microbial communities,” Annual Review of Genetics, vol. 38, pp. 525-552, 2004. · doi:10.1146/annurev.genet.38.072902.091216
[31] M. W. Kirschner, “The meaning of systems biology,” Cell, vol. 121, no. 4, pp. 503-504, 2005. · doi:10.1016/j.cell.2005.05.005
[32] A. W. Cowley Jr., “The elusive field of systems biology,” Physiological Genomics, vol. 16, pp. 285-286, 2004. · doi:10.1152/physiolgenomics.00007.2004
[33] P. Kohl, E. J. Crampin, T. A. Quinn, and D. Noble, “Systems biology: an approach,” Clinical Pharmacology and Therapeutics, vol. 88, no. 1, pp. 25-33, 2010. · doi:10.1038/clpt.2010.92
[34] V. A. McKusick and F. H. Ruddle, “A new discipline, a new name, a new journal,” Genomics, vol. 1, no. 1, pp. 1-2, 1987.
[35] A. M. Maxam and W. Gilbert, “A new method for sequencing DNA,” Proceedings of the National Academy of Sciences of the United States of America, vol. 74, no. 2, pp. 560-564, 1977.
[36] F. Sanger and A. R. Coulson, “A rapid method for determining sequences in DNA by primed synthesis with DNA polymerase,” Journal of Molecular Biology, vol. 94, no. 3, pp. 441-448, 1975.
[37] L. M. Smith, J. Z. Sanders, R. J. Kaiser, et al., “Fluorescence detection in automated DNA sequence analysis,” Nature, vol. 321, no. 6071, pp. 674-679, 1986.
[38] L. E. Hood, M. W. Hunkapiller, and L. M. Smith, “Automated DNA sequencing and analysis of the human genome,” Genomics, vol. 1, no. 3, pp. 201-212, 1987.
[39] F. S. Collins, M. Morgan, and A. Patrinos, “The human genome project: lessons from large-scale biology,” Science, vol. 300, no. 5617, pp. 286-290, 2003. · doi:10.1126/science.1084564
[40] P. Hieter and M. Boguski, “Functional genomics: it’s all how you read it,” Science, vol. 278, no. 5338, pp. 601-602, 1997. · doi:10.1126/science.278.5338.601
[41] S. Rastan and L. J. Beeley, “Functional genomics: going forwards from the databases,” Current Opinion in Genetics and Development, vol. 7, no. 6, pp. 777-783, 1997. · doi:10.1016/S0959-437X(97)80040-8
[42] C. Somerville and S. Somerville, “Plant functional genomics,” Science, vol. 285, no. 5426, pp. 380-383, 1999. · doi:10.1126/science.285.5426.380
[43] R. Brent, “Genomic biology,” Cell, vol. 100, no. 1, pp. 169-183, 2000.
[44] P. E. Griffiths and K. Stotz, “Genes in the postgenomic era,” Theoretical Medicine and Bioethics, vol. 27, no. 6, pp. 499-521, 2006. · doi:10.1007/s11017-006-9020-y
[45] G. P. Rédei, C. Koncz, and J. D. Phillips, “Changing images of the gene,” Advances in Genetics, vol. 56, pp. 53-100, 2006. · doi:10.1016/S0065-2660(06)56002-X
[46] T. R. Gingeras, “Origin of phenotypes: genes and transcripts,” Genome Research, vol. 17, no. 6, pp. 682-690, 2007. · doi:10.1101/gr.6525007
[47] M. B. Gerstein, C. Bruce, J. S. Rozowsky et al., “What is a gene, post-ENCODE? History and updated definition,” Genome Research, vol. 17, no. 6, pp. 669-681, 2007. · doi:10.1101/gr.6339607
[48] P. Portin, “The elusive concept of the gene,” Hereditas, vol. 146, no. 3, pp. 112-117, 2009. · doi:10.1111/j.1601-5223.2009.02128.x
[49] P. Carninci, “Tagging mammalian transcription complexity,” Trends in Genetics, vol. 22, no. 9, pp. 501-510, 2006. · doi:10.1016/j.tig.2006.07.003
[50] P. Kapranov, A. T. Willingham, and T. R. Gingeras, “Genome-wide transcription and the implications for genomic organization,” Nature Reviews Genetics, vol. 8, no. 6, pp. 413-423, 2007. · doi:10.1038/nrg2083
[51] J. C. Avise, “Evolving genomic metaphors: a new look at the language of DNA,” Science, vol. 294, no. 5540, pp. 86-87, 2001. · doi:10.1126/science.294.5540.86
[52] P. P. Amaral, M. E. Dinger, T. R. Mercer, and J. S. Mattick, “The eukaryotic genome as an RNA machine,” Science, vol. 319, no. 5871, pp. 1787-1789, 2008. · doi:10.1126/science.1155472
[53] J. S. Mattick, “The functional genomics of noncoding RNA,” Science, vol. 309, no. 5740, pp. 1527-1528, 2005. · doi:10.1126/science.1117806
[54] K. C. Martin and A. Ephrussi, “mRNA localization: gene expression in the spatial dimension,” Cell, vol. 136, no. 4, pp. 719-730, 2009. · doi:10.1016/j.cell.2009.01.044
[55] Y. Lazebnik, “Can a biologist fix a radio?-Or, what I learned while studying apoptosis,” Cancer Cell, vol. 2, no. 3, pp. 179-182, 2002. · doi:10.1016/S1535-6108(02)00133-2
[56] G. Weng, U. S. Bhalla, and R. Iyengar, “Complexity in biological signaling systems,” Science, vol. 284, no. 5411, pp. 92-96, 1999. · doi:10.1126/science.284.5411.92
[57] G. M. Whitesides and R. F. Ismagilov, “Complexity in chemistry,” Science, vol. 284, no. 5411, pp. 89-92, 1999. · doi:10.1126/science.284.5411.89
[58] J. Ross and A. P. Arkin, “Complex systems: from chemistry to systems biology,” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 16, pp. 6433-6434, 2009. · doi:10.1073/pnas.0903406106
[59] N. Goldenfeld and L. P. Kadanoff, “Simple lessons from complexity,” Science, vol. 284, no. 5411, pp. 87-89, 1999. · doi:10.1126/science.284.5411.87
[60] J. I. Castrillo and S. G. Oliver, “Metabolomics and systems biology in Saccharomyces cerevisiae,” in The Mycota: A Comprehensive Treatise on Fungi as Experimental Systems for Basic and Applied Research, A. J. P. Brown, Ed., pp. 3-18, Springer, Heidelberg, Germany, 2006.
[61] T. Ideker, V. Thorsson, J. A. Ranish et al., “Integrated genomic and proteomic analyses of a systematically perturbed metabolic network,” Science, vol. 292, no. 5518, pp. 929-934, 2001. · doi:10.1126/science.292.5518.929
[62] H. Ge, A. J. M. Walhout, and M. Vidal, “Integrating ’omic’ information: a bridge between genomics and systems biology,” Trends in Genetics, vol. 19, no. 10, pp. 551-560, 2003. · doi:10.1016/j.tig.2003.08.009
[63] C. L. de Hoog and M. Mann, “Proteomics,” Annual Review of Genomics and Human Genetics, vol. 5, pp. 267-293, 2004. · doi:10.1146/annurev.genom.4.070802.110305
[64] F. J. Bruggeman and H. V. Westerhoff, “The nature of systems biology,” Trends in Microbiology, vol. 15, no. 1, pp. 45-50, 2007. · doi:10.1016/j.tim.2006.11.003
[65] T. Ideker and D. Lauffenburger, “Building with a scaffold: emerging strategies for high- to low-level cellular modeling,” Trends in Biotechnology, vol. 21, no. 6, pp. 255-262, 2003. · doi:10.1016/S0167-7799(03)00115-X
[66] R. Laubenbacher and A. S. Jarrah, “Algebraic models of biochemical networks,” Methods in Enzymology, vol. 467, no. C, pp. 163-196, 2009. · doi:10.1016/S0076-6879(09)67007-5
[67] S. Huang, “Back to the biology in systems biology: what can we learn from biomolecular networks?” Brief Funct Genomic Proteomic, vol. 2, no. 4, pp. 279-297, 2004.
[68] M. A. O’Malley and J. Dupré, “Fundamental issues in systems biology,” BioEssays, vol. 27, no. 12, pp. 1270-1276, 2005. · doi:10.1002/bies.20323
[69] R. M. May, “Uses and abuses of mathematics in biology,” Science, vol. 303, no. 5659, pp. 790-793, 2004. · doi:10.1126/science.1094442
[70] J. J. Tyson, K. Chen, and B. Novak, “Network dynamics and cell physiology,” Nature Reviews Molecular Cell Biology, vol. 2, no. 12, pp. 908-916, 2001. · doi:10.1038/35103078
[71] K. C. Chen, L. Calzone, A. Csikasz-Nagy, F. R. Cross, B. Novak, and J. J. Tyson, “Integrative analysis of cell cycle control in budding yeast,” Molecular Biology of the Cell, vol. 15, no. 8, pp. 3841-3862, 2004. · doi:10.1091/mbc.E03-11-0794
[72] E. Klipp, B. Nordlander, R. Krüger, P. Gennemark, and S. Hohmann, “Integrative model of the response of yeast to osmotic shock,” Nature Biotechnology, vol. 23, no. 8, pp. 975-982, 2005. · doi:10.1038/nbt1114
[73] A. M. Feist, C. S. Henry, J. L. Reed et al., “A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information,” Molecular Systems Biology, vol. 3, article 121, 2007. · doi:10.1038/msb4100155
[74] B. M. Bakker, P. A. M. Michels, F. R. Opperdoes, and H. V. Westerhoff, “What controls glycolysis in bloodstream form Trypanosoma brucei?” Journal of Biological Chemistry, vol. 274, no. 21, pp. 14551-14559, 1999. · doi:10.1074/jbc.274.21.14551
[75] N. C. Duarte, M. J. Herrgård, and B. Ø. Palsson, “Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model,” Genome Research, vol. 14, no. 7, pp. 1298-1309, 2004. · doi:10.1101/gr.2250904
[76] B. Teusink, J. Passarge, C. A. Reijenga et al., “Can yeast glycolysis be understood terms of vitro kinetics of the constituent enzymes? Testing biochemistry,” European Journal of Biochemistry, vol. 267, no. 17, pp. 5313-5329, 2000. · doi:10.1046/j.1432-1327.2000.01527.x
[77] K. Smallbone, E. Simeonidis, N. Swainston, and P. Mendes, “Towards a genome-scale kinetic model of cellular metabolism,” BMC Systems Biology, vol. 4, article 6, 2010. · doi:10.1186/1752-0509-4-6
[78] L. H. Hartwell, J. J. Hopfield, S. Leibler, and A. W. Murray, “From molecular to modular cell biology,” Nature, vol. 402, no. 6761, pp. C47-C52, 1999.
[79] J. J. Hornberg, F. J. Bruggeman, H. V. Westerhoff, and J. Lankelma, “Cancer: a systems biology disease,” BioSystems, vol. 83, no. 2-3, pp. 81-90, 2006. · doi:10.1016/j.biosystems.2005.05.014
[80] P. Kohl and D. Noble, “Systems biology and the virtual physiological human,” Molecular Systems Biology, vol. 5, article 292, 2009. · doi:10.1038/msb.2009.51
[81] Y. L. Sang, D.-Y. Lee, and Y. K. Tae, “Systems biotechnology for strain improvement,” Trends in Biotechnology, vol. 23, no. 7, pp. 349-358, 2005. · doi:10.1016/j.tibtech.2005.05.003
[82] C. A. Argmann, P. Chambon, and J. Auwerx, “Mouse phenogenomics: the fast track to ”systems metabolism”,” Cell Metabolism, vol. 2, no. 6, pp. 349-360, 2005. · doi:10.1016/j.cmet.2005.11.002
[83] J. M. Zahn and S. K. Kim, “Systems biology of aging in four species,” Current Opinion in Biotechnology, vol. 18, no. 4, pp. 355-359, 2007. · doi:10.1016/j.copbio.2007.07.004
[84] J. S. Yuan, D. W. Galbraith, S. Y. Dai, P. Griffin, and C. N. Stewart Jr., “Plant systems biology comes of age,” Trends in Plant Science, vol. 13, no. 4, pp. 165-171, 2008. · doi:10.1016/j.tplants.2008.02.003
[85] F. Hynne, S. Danø, and P. G. Sørensen, “Full-scale model of glycolysis in Saccharomyces cerevisiae,” Biophysical Chemistry, vol. 94, no. 1-2, pp. 121-163, 2001. · doi:10.1016/S0301-4622(01)00229-0
[86] M.-A. Albert, J. R. Haanstra, V. Hannaert et al., “Experimental and in silico analyses of glycolytic flux control in bloodstream form Trypanosoma brucei,” Journal of Biological Chemistry, vol. 280, no. 31, pp. 28306-28315, 2005. · doi:10.1074/jbc.M502403200
[87] P. S. Kim, D. Levy, and P. P. Lee, “Modeling and simulation of the immune system as a self-regulating network,” Methods in Enzymology, vol. 467, no. C, pp. 79-109, 2009. · doi:10.1016/S0076-6879(09)67004-X
[88] D. Noble, “Modeling the heart-from genes to cells to the whole organ,” Science, vol. 295, no. 5560, pp. 1678-1682, 2002. · doi:10.1126/science.1069881
[89] B. Schwikowski, P. Uetz, and S. Fields, “A network of protein-protein interactions in yeast,” Nature Biotechnology, vol. 18, no. 12, pp. 1257-1261, 2000. · doi:10.1038/82360
[90] T. I. Lee, N. J. Rinaldi, F. Robert et al., “Transcriptional regulatory networks in Saccharomyces cerevisiae,” Science, vol. 298, no. 5594, pp. 799-804, 2002. · doi:10.1126/science.1075090
[91] M. Güell, V. van Noort, E. Yus et al., “Transcriptome complexity in a genome-reduced bacterium,” Science, vol. 326, no. 5957, pp. 1268-1271, 2009. · doi:10.1126/science.1176951
[92] S. Kühner, V. van Noort, M. J. Betts et al., “Proteome organization in a genome-reduced bacterium,” Science, vol. 326, no. 5957, pp. 1235-1240, 2009. · doi:10.1126/science.1176343
[93] E. Yus, T. Maier, K. Michalodimitrakis et al., “Impact of genome reduction on bacterial metabolism and its regulation,” Science, vol. 326, no. 5957, pp. 1263-1268, 2009. · doi:10.1126/science.1177263
[94] S. S. Shen-Orr, R. Milo, S. Mangan, and U. Alon, “Network motifs in the transcriptional regulation network of Escherichia coli,” Nature Genetics, vol. 31, no. 1, pp. 64-68, 2002. · doi:10.1038/ng881
[95] N. J. Krogan, G. Cagney, H. Yu et al., “Global landscape of protein complexes in the yeast Saccharomyces cerevisiae,” Nature, vol. 440, no. 7084, pp. 637-643, 2006. · doi:10.1038/nature04670
[96] K. Tarassov, V. Messier, C. R. Landry et al., “An in vivo map of the yeast protein interactome,” Science, vol. 320, no. 5882, pp. 1465-1470, 2008. · doi:10.1126/science.1153878
[97] Y. Tang, F. Pingitore, A. Mukhopadhyay, R. Phan, T. C. Hazen, and J. D. Keasling, “Pathway confirmation and flux analysis of central metabolic pathways in Desulfovibrio vulgaris Hildenborough using gas chromatography-mass spectrometry and Fourier transform-ion cyclotron resonance mass spectrometry,” Journal of Bacteriology, vol. 189, no. 3, pp. 940-949, 2007. · doi:10.1128/JB.00948-06
[98] T. del Castillo, J. L. Ramos, J. J. Rodríguez-Herva, T. Fuhrer, U. Sauer, and E. Duque, “Convergent peripheral pathways catalyze initial glucose catabolism in Pseudomonas putida: genomic and flux analysis,” Journal of Bacteriology, vol. 189, no. 14, pp. 5142-5152, 2007. · doi:10.1128/JB.00203-07
[99] O. Schilling, O. Frick, C. Herzberg et al., “Transcriptional and metabolic responses of Bacillus subtilis to the availability of organic acids: transcription regulation is important but not sufficient to account for metabolic adaptation,” Applied and Environmental Microbiology, vol. 73, no. 2, pp. 499-507, 2007. · doi:10.1128/AEM.02084-06
[100] N. Saito, M. Robert, H. Kochi et al., “Metabolite profiling reveals YihU as a novel hydroxybutyrate dehydrogenase for alternative succinic semialdehyde metabolism in Escherichia coli,” Journal of Biological Chemistry, vol. 284, no. 24, pp. 16442-16451, 2009. · doi:10.1074/jbc.M109.002089
[101] M. Krantz, D. Ahmadpour, L.-G. Ottosson et al., “Robustness and fragility in the yeast high osmolarity glycerol (HOG) signal-transduction pathway,” Molecular Systems Biology, vol. 5, article 281, 2009. · doi:10.1038/msb.2009.36
[102] T. Koide, T. Hayata, and K. W. Y. Cho, “Xenopus as a model system to study transcriptional regulatory networks,” Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 14, pp. 4943-4948, 2005. · doi:10.1073/pnas.0408125102
[103] L. Giot, J. S. Bader, C. Brouwer et al., “A protein interaction map of Drosophila melanogaster,” Science, vol. 302, no. 5651, pp. 1727-1736, 2003. · doi:10.1126/science.1090289
[104] Y. J. Tang, R. Chakraborty, H. G. Martín, J. Chu, T. C. Hazen, and J. D. Keasling, “Flux analysis of central metabolic pathways in Geobacter metallireducens during reduction of soluble Fe(III)-nitrilotriacetic acid,” Applied and Environmental Microbiology, vol. 73, no. 12, pp. 3859-3864, 2007. · doi:10.1128/AEM.02986-06
[105] B. B. Aldridge, J. M. Burke, D. A. Lauffenburger, and P. K. Sorger, “Physicochemical modelling of cell signalling pathways,” Nature Cell Biology, vol. 8, no. 11, pp. 1195-1203, 2006. · doi:10.1038/ncb1497
[106] N. Ishii, K. Nakahigashi, T. Baba et al., “Multiple high-throughput analyses monitor the response of E. coli to perturbations,” Science, vol. 316, no. 5824, pp. 593-597, 2007. · doi:10.1126/science.1132067
[107] S. Tännler, E. Fischer, D. Le Coq et al., “CcpN controls central carbon fluxes in Bacillus subtilis,” Journal of Bacteriology, vol. 190, no. 18, pp. 6178-6187, 2008. · doi:10.1128/JB.00552-08
[108] H. Ochman and R. Raghavan, “Systems biology. Excavating the functional landscape of bacterial cells,” Science, vol. 326, no. 5957, pp. 1200-1201, 2009. · doi:10.1126/science.1183757
[109] G. Stephanopoulos, “Metabolic fluxes and metabolic engineering,” Metabolic Engineering, vol. 1, no. 1, pp. 1-11, 1999. · doi:10.1006/mben.1998.0101
[110] U. Sauer, “Metabolic networks in motion: 13C-based flux analysis,” Molecular Systems Biology, vol. 2, article 62, 2006. · doi:10.1038/msb4100109
[111] E. P. Gianchandani, D. L. Brautigan, and J. A. Papin, “Systems analyses characterize integrated functions of biochemical networks,” Trends in Biochemical Sciences, vol. 31, no. 5, pp. 284-291, 2006. · doi:10.1016/j.tibs.2006.03.007
[112] N.-M. Grüning, H. Lehrach, and M. Ralser, “Regulatory crosstalk of the metabolic network,” Trends in Biochemical Sciences, vol. 35, no. 4, pp. 220-227, 2010. · doi:10.1016/j.tibs.2009.12.001
[113] J. Nielsen and S. Oliver, “The next wave in metabolome analysis,” Trends in Biotechnology, vol. 23, no. 11, pp. 544-546, 2005. · doi:10.1016/j.tibtech.2005.08.005
[114] N. Zamboni and U. Sauer, “Novel biological insights through metabolomics and 13C-flux analysis,” Current Opinion in Microbiology, vol. 12, no. 5, pp. 553-558, 2009. · doi:10.1016/j.mib.2009.08.003
[115] W. Wiechert and K. Nöh, “From stationary to instationary metabolic flux analysis,” Advances in Biochemical Engineering/Biotechnology, vol. 92, pp. 145-172, 2005.
[116] Y. J. Tang, H. G. Martin, S. Myers, S. Rodriguez, E. E. K. Baidoo, and J. D. Keasling, “Advances in analysis of microbial metabolic fluxes via 13C isotopic labeling,” Mass Spectrometry Reviews, vol. 28, no. 2, pp. 362-375, 2009. · doi:10.1002/mas.20191
[117] M. R. Antoniewicz, J. K. Kelleher, and G. Stephanopoulos, “Elementary metabolite units (EMU): a novel framework for modeling isotopic distributions,” Metabolic Engineering, vol. 9, no. 1, pp. 68-86, 2007. · doi:10.1016/j.ymben.2006.09.001
[118] J. D. Young, J. L. Walther, M. R. Antoniewicz, H. Yoo, and G. Stephanopoulos, “An elementary metabolite unit (EMU) based method of isotopically nonstationary flux analysis,” Biotechnology and Bioengineering, vol. 99, no. 3, pp. 686-699, 2008. · doi:10.1002/bit.21632
[119] M. Hucka, A. Finney, B. J. Bornstein et al., “Evolving a lingua franca and associated software infrastructure for computational systems biology: the Systems Biology Markup Language (SBML) project,” Systems Biology, vol. 1, no. 1, pp. 41-53, 2004. · doi:10.1049/sb:20045008
[120] N. L. Novère, M. Hucka, H. Mi et al., “The systems biology graphical notation,” Nature Biotechnology, vol. 27, no. 8, pp. 735-741, 2009. · doi:10.1038/nbt.1558
[121] H. M. Sauro, M. Hucka, A. Finney et al., “Next generation simulation tools: the systems biology workbench and BioSPICE integration,” OMICS, vol. 7, no. 4, pp. 355-372, 2003.
[122] A. Funahashi, M. Morohashi, H. Kitano, and N. Tanimura, “CellDesigner: a process diagram editor for gene-regulatory and biochemical networks,” BIOSILICO, vol. 1, pp. 159-162, 2003.
[123] P. Mendes, S. Hoops, S. Sahle, R. Gauges, J. Dada, and U. Kummer, “Computational modeling of biochemical networks using COPASI,” Methods in Molecular Biology, vol. 500, pp. 17-59, 2009.
[124] D. A. Benson, I. Karsch-Mizrachi, D. J. Lipman, J. Ostell, and E. W. Sayers, “GenBank,” Nucleic Acids Research, vol. 37, no. 1, pp. D26-D31, 2010. · Zbl 05746496 · doi:10.1093/nar/gkn723
[125] A. Kouranov, L. Xie, J. de la Cruz et al., “The RCSB PDB information portal for structural genomics,” Nucleic Acids Research, vol. 34, pp. D302-D305, 2006.
[126] R. D. Finn, J. Mistry, J. Tate et al., “The Pfam protein families database,” Nucleic Acids Research, vol. 38, supplement 1, pp. D211-D222, 2010. · Zbl 05891933 · doi:10.1093/nar/gkp985
[127] R. Caspi, T. Altman, J. M. Dale et al., “The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases,” Nucleic Acids Research, vol. 38, supplement 1, pp. D473-D479, 2010. · Zbl 05891976 · doi:10.1093/nar/gkp875
[128] L. Matthews, G. Gopinath, M. Gillespie et al., “Reactome knowledgebase of human biological pathways and processes,” Nucleic Acids Research, vol. 37, no. 1, pp. D619-D622, 2009. · Zbl 05746600 · doi:10.1093/nar/gkn863
[129] M. Kuhn, D. Szklarczyk, A. Franceschini et al., “STITCH 2: an interaction network database for small molecules and proteins,” Nucleic Acids Research, vol. 38, supplement 1, pp. D552-D556, 2010. · Zbl 05891989 · doi:10.1093/nar/gkp937
[130] B. Lehne and T. Schlitt, “Protein-protein interaction databases: keeping up with growing interactomes,” Human Genomics, vol. 3, no. 3, pp. 291-297, 2009.
[131] N. Le Novère, B. Bornstein, A. Broicher et al., “BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems,” Nucleic Acids Research, vol. 34, pp. D689-D691, 2006.
[132] P. Shannon, A. Markiel, O. Ozier et al., “Cytoscape: a software Environment for integrated models of biomolecular interaction networks,” Genome Research, vol. 13, no. 11, pp. 2498-2504, 2003. · doi:10.1101/gr.1239303
[133] P. D. Karp, S. M. Paley, M. Krummenacker et al., “Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology,” Briefings in Bioinformatics, vol. 11, no. 1, pp. 40-79, 2009. · doi:10.1093/bib/bbp043
[134] J. L. Reed and B. Ø. Palsson, “Thirteen years of building constraint-based in silico models of Escherichia coli,” Journal of Bacteriology, vol. 185, no. 9, pp. 2692-2699, 2003. · doi:10.1128/JB.185.9.2692-2699.2003
[135] C. H. Schilling, J. S. Edwards, and B. O. Palsson, “Toward metabolic phenomics: analysis of genomic data using flux balances,” Biotechnology Progress, vol. 15, no. 3, pp. 288-295, 1999. · doi:10.1021/bp9900357
[136] P. Dolezal, V. Likic, J. Tachezy, and T. Lithgow, “Evolution of the molecular machines for protein import into mitochondria,” Science, vol. 313, no. 5785, pp. 314-318, 2006. · doi:10.1126/science.1127895
[137] J. Nielsen, “Systems biology of lipid metabolism: from yeast to human,” FEBS Letters, vol. 583, no. 24, pp. 3905-3913, 2009. · doi:10.1016/j.febslet.2009.10.054
[138] Y. Ohashi, A. Hirayama, T. Ishikawa et al., “Depiction of metabolome changes in histidine-starved Escherichia coli by CE-TOFMS,” Molecular BioSystems, vol. 4, no. 2, pp. 135-147, 2008. · doi:10.1039/b714176a
[139] P. Brazhnik, A. de la Fuente, and P. Mendes, “Gene networks: how to put the function in genomics,” Trends in Biotechnology, vol. 20, no. 11, pp. 467-472, 2002. · doi:10.1016/S0167-7799(02)02053-X
[140] E. Alm and A. P. Arkin, “Biological networks,” Current Opinion in Structural Biology, vol. 13, no. 2, pp. 193-202, 2003. · doi:10.1016/S0959-440X(03)00031-9
[141] S. Wullschleger, R. Loewith, and M. N. Hall, “TOR signaling in growth and metabolism,” Cell, vol. 124, no. 3, pp. 471-484, 2006. · doi:10.1016/j.cell.2006.01.016
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.