Small GTPases (original) (raw)

Abstract

S-adenosylmethionine (Fig. 1) is synthesized from ATP and L-methionine and acts as a donor of methyl groups in prokaryote as well as eukaryote. By the transfer of a methyl group, S-adenosylmethionine is converted into S-adenosylhomocysteine, which is broken down to homocysteine and adenosine. Homocysteine is then converted to methionine. S-adenosylmethionine is also used for synthesis of cysteine as well as polyamines.

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References (336)

  1. Bak P (1996) How Nature Works: The Science of Self- Organized Criticality. Copernicus Books
  2. Camazine S, Deneubourg J-L, Franks NR, Sneyd J, Theraulaz G, Bonabeau E (2001) Self-organization in biological systems. Princeton University Press, Princeton
  3. Epstein IR, Vanag VK (2005) Complex patterns in reactive microemulsions: self-organized nanostructures? Chaos 15, 047510-1-7
  4. Fry I (2000) The emergence of life on Earth: a historical and scientific overview. Rutgers University Press, London
  5. Haken H (1983) Synergetics: nonequilibrium phase transitions and self-organization in physics, chemistry, and biology. Springer, Berlin
  6. Hanczyc MM, Toyota T, Ikegami T, Packard N, Sugawara T (2007) Fatty acid chemistry at the oil-water interface: self- propelled oil droplets. JACS 129:9386-9391
  7. Kauffman S (1993) The origins of order: self-organization and selection in evolution. Oxford University Press, Oxford
  8. Karsenti E (2008) Self-organization in cell biology. A brief history. Nat Rev 9:255-262
  9. Kelso JAS (1995) Dynamic patterns: the self-organization of brain and behavior. MIT Press, Cambridge, MA
  10. Lehn J-M (1995) Supramolecular chemistry: concepts and perspectives. Wiley, New York Ludlow RF, Otto S (2008) Systems chemistry. Chem Soc Rev 37:101-108
  11. Nicolis G, Prigogine I (1977) Self-organization in non- equilibrium systems. Wiley, New York Ruiz-Mirazo K, Pereto ´J, Moreno A (2004) A universal defini- tion of life: autonomy and open-ended evolution. Orig Life Evol Biosph 34:323-346
  12. Sole ´RV, Bascompte J (2006) Self-organization in complex ecosystems. Princeton University Press, Princeton Turing AM (1952) The chemical basis of morphogenesis. Philos Trans R Soc Lond B 237:37-72
  13. Yates FE (ed) (1987) Self-organizing systems. The emergence of order. Plenum Press, New York References
  14. Von Neumann J (1966) Theory of self-reproducing automata. University of Illinois Press, Urbana/London References
  15. Mandelbrot B (1967) How long is the coast of Britain? Statistical self-similarity and fractional dimension. Science 156: 636-638
  16. Gunawan R, Cao Y, Petzold L, Doyle FJ III (2005) Sensitivity analysis of discrete stochastic systems. Biophys J 88: 2530-540
  17. Govind CK, Qiu H, Ginsburg DS, Ruan C, Hofmeyer K, Hu C, Swaminathan V, Workman JL, Li B, Hinnebusch AG (2010) Phosphorylated Pol II CTD recruits multiple HDACs, including Rpd3C(S), for methylation-dependent deacetylation of ORF nucleosomes. Mol Cell 39(2):234-46
  18. Pijnappel WW, Schaft D, Roguev A, Shevchenko A, Tekotte H, Wilm M, Rigaut G, Se ´raphin B, Aasland R, Stewart AF (2001) The S. cerevisiae SET3 complex includes two histone deacetylases, Hos2 and Hst1, and is a meiotic-specific repres- sor of the sporulation gene program. Genes Dev 15(22):2991-3004
  19. Fisher RA (1915) The evolution of sexual preference. Eugen Rev 7:184-192
  20. Grafen A (1990) Biological signals as handicaps. J Theor Biol 144:517-546
  21. Zahavi A, Zahavi A (1997) The handicap principle: a missing piece of Darwin's puzzle. Oxford University Press, Oxford References
  22. Alberts B, Johnson A, Lewis J, Raff M, Roberts K, Walter P (2008) Molecular biology of the cell, 5th edn. Garland Science, New York
  23. Nagai K, Oubridge C, Kuglstatter A, Menichelli E, Isel C, Jovine L (2003) Structure, function and evolution of the signal recognition particle. EMBO J 22:3479-3485 Signal Transduction ▶ Signal Transduction Pathway Signal Recognition Particle, Fig. 1 Signal recognition particle of (a) mammal, (b) Archaea, and (c) E. coli References
  24. Snoep JL (2005) The silicon cell initiative: working towards a detailed kinetic description at the cellular level. Curr Opin Biotechnol 16:336-343
  25. Snoep JL, Westerhoff HV (2004) The silicon cell initiative. Curr Genomics 5:687-697
  26. Westerhoff HV, Bruggeman F, Hofmeyr JH, Snoep JL (2003) Attractive models: how to make the silicon cell rele- vant and dynamic. Comp Funct Genomics 4(1):155-158 References SOAP Version 1.2 Part 1: Messaging framework (Second Edition), W3C Recommendation 27 Apr 2007. http://www. w3.org/TR/soap12-part1/ References
  27. Sharda R, Voß S, Woodruff DL, Fink A (2003) Optimization software class libraries. Springer, Berlin, pp 91-94
  28. Zhilinskas A, Z ˇilinskas A (2008) Stochastic global optimization. Springer, New York, pp 103-124
  29. Chamberlain G, Fox J, Ashton B, Middleton J (2007) Concise review: mesenchymal stem cells: their phenotype, differen- tiation capacity, immunological features, and potential for homing. Stem Cells 25:2739-2749
  30. Ema H, Morita Y, Yamazaki S, Matsubara A, Seita J, Tadokoro Y, Kondo H, Takano H, Nakauchi H (2006) Adult mouse hema- topoietic stem cells: purification and single-cell assays. Nat Protoc 1:2979-2987
  31. Minguell JJ, Erices A, Conget P (2001) Mesenchymal stem cells. Exp Biol Med (Maywood) 226:507-520
  32. Pochampally R (2008) Colony forming unit assays for MSCs. Methods Mol Biol 449:83-91
  33. Soleimani M, Nadri S (2009) A protocol for isolation and culture of mesenchymal stem cells from mouse bone marrow. Nat Protoc 4:102-106
  34. Uccelli A, Moretta L, Pistoia V (2008) Mesenchymal stem cells in health and disease. Nat Rev Immunol 8:726-736
  35. Berglund N, Gentz B (2006) Noise-induced phenomena in slow-fast dynamical systems: a sample-paths approach. Springer, London
  36. Cohen R, Havlin S (2003) Scale-free networks are ultrasmall. Phys Rev Lett 90(5):058701
  37. Jeong H, Mason SP, Barabasi AL, Oltvai ZN (2001) Lethality and centrality in protein networks. Nature 411(6833):41-42
  38. Khanin R, Wit E (2006) How scale-free are biological networks. J Comput Biol 13(3):810-818
  39. Monasson R (1999) Diffusion, localization and dispersion rela- tions on "small-world" lattices. Eur Phys J B 12:555-567
  40. Newman MEJ (2000) Models of the small world: A review. eprint arXiv:cond-mat/0001118
  41. Newman MEJ, Watts DJ (1999) Renormalization group analysis of the small-world network model. Phys Lett A 263(4-6): 341-346
  42. Tong AH, Lesage G, Bader GD, Ding H, Xu H, Xin X, Young J, Berriz GF, Brost RL, Chang M, Chen Y, Cheng X, Chua G, Friesen H, Goldberg DS, Haynes J, Humphries C, He G, Hussein S, Ke L, Krogan N, Li Z, Levinson JN, Lu H, Me ´nard P, Munyana C, Parsons AB, Ryan O, Tonikian R, Roberts T, Sdicu AM, Shapiro J, Sheikh B, Suter B, Wong SL, Zhang LV, Zhu H, Burd CG, Munro S, Sander C, Rine J, Greenblatt J, Peter M, Bretscher A, Bell G, Roth FP, Brown GW, Andrews B, Bussey H, Boone C (2004) Global mapping of the yeast genetic interaction network. Science 303(5659):808-813
  43. Wagner A, Fell DA (2001) The small world inside large metabolic networks. Proc R Soc B: Biol Sci 268(1478): 1803-1810
  44. Watts DJ, Strogatz SH (1998) Collective dynamics of 'small- world' networks. Nature 393(6684):440-442
  45. Yook SHH, Oltvai ZN, Baraba ´si ALL (2004) Functional and topological characterization of protein interaction networks. Proteomics 4(4):928-942
  46. Moore SD, Sauer RT (2007) The tmRNA system for transla- tional surveillance and ribosome rescue. Annu Rev Biochem 76:101-124
  47. Shpanchenko OV, Golovin AV, Bugaeva EY, Isaksson LA, Dontsova OA (2010) Structural aspects of trans-translation. IUBMB Life 62:120-124
  48. SnoRNA Databases ▶ Non-coding RNA Databases References Cariaso M, Lennon G (2011) SNPedia. World Wide Web URL: http://www.SNPedia.com/. Accessed 1 May 2011
  49. Check Hayden E (2008) How to get the most from a gene test. Nature 456(7218):11
  50. Cariaso M (2007) SNPedia: a wiki for personal genomics. Bio-IT World, 17 Dec 2007
  51. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM, Perry JR, Elliott KS, Lango H, Rayner NW, Shields B, Harries LW, Barrett JC, Ellard S, Groves CJ, Knight B, Patch AM, Ness AR, Ebrahim S, Lawlor DA, Ring SM, Ben-Shlomo Y, Jarvelin MR, Sovio U, Bennett AJ, Melzer D, Ferrucci L, Loos RJ, Barroso I, Wareham NJ, Karpe F, Owen KR, Cardon LR, Walker M, Hitman GA, Palmer CN, Doney AS, Morris AD, Smith GD, Hattersley AT, McCarthy MI (2007) A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316(5826):889-894, Epub 2007 Apr 12
  52. SNPs ▶ Single Nucleotide Polymorphisms
  53. SNPedia, Fig. 1 A screenshot of a sample SNP page from SNPedia Website References
  54. Haken H (2004) Synergetics. Introduction and advanced topics. Springer, Berlin
  55. Mikhailov A, Loskutov A (1996) Foundations of synergetics II: chaos and noise. Springer, Berlin
  56. Murray JD (2002) Mathematical biology. Springer, Berlin References Bashton M, Thornton JM (2009) Domain-ligand mapping for enzymes. J Mol Recognit 23:194-208
  57. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN et al (2000) The protein data bank. Nucleic Acids Res 28:235-242
  58. Feist AM, Herrgard MJ, Thiele I, Reed JL, Palsson BO (2009) Reconstruction of biochemical networks in microor- ganisms. Nat Rev Microbiol 7:129-143
  59. Goldberg RN, Tewari YB, Bhat TN (2004) Thermodynamics of enzyme-catalyzed reactions -a database for quantitative biochemistry. Bioinformatics 20:2874-2877
  60. Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC et al (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19:524-531
  61. Reed JL, Famili I, Thiele I, Palsson BO (2006) Towards multidimensional genome annotation. Nat Rev Genet 7:130-141
  62. Rojas I, Golebiewski M, Kania R, Krebs O, Mir S et al (2007) SABIO-RK: a database for biochemical reactions and their kinetics. BMC Syst Biol 1(Suppl 1):26
  63. Scheer M, Grote A, Chang A, Schomburg I, Munaretto C et al (2011) BRENDA, the enzyme information system in 2011, Nucleic acids research. Nucleic Acids Res 39:D670-D676
  64. Schellenberger J, Park JO, Conrad TM, Palsson BO (2010) BiGG: a biochemical genetic and genomic knowledgebase of large scale metabolic reconstructions. BMC Bioinformatics 11:213
  65. Wishart DS, Knox C, Guo AC, Eisner R, Young N et al (2009) HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res 37:D603-D610 Specific Response Jinzhi Lei Zhou Pei-Yuan Center for Applied Mathematics, Tsinghua University of Beijing, Beijing, China References Bardwell L, Zou X, Nie Q, Komarova NL (2007) Mathematical models of specificity in cell signaling. Biophys J 92:3425-3441
  66. Komarova NL, Zou X, Nie Q, Bardwell L (2005) A theoretical framework for specificity in cell signaling. Mol Syst Biol 1:2005.0023
  67. S 1966 Specific Response
  68. Ade H (1998) Experimental methods in the physical sciences, vol 32. Academic, USA
  69. Breusegem SY, Levi M, Barry NP (2006) Fluorescence correla- tion spectroscopy and fluorescence lifetime imaging micros- copy. Nephron Exp Nephrol 103:e41-e49
  70. Ellis DI, Goodacre R (2006) Metabolic fingerprinting in disease diagnosis: biomedical applications of infrared and Raman spectroscopy. Analyst 131(8):875-885
  71. Grude O, Hammiche A, Pollock H, Bentley AJ, Walsh MJ, Martin FL, Fullwood NJ (2007) Near-field photothermal microspectroscopy for adult stem-cell identification and characterization. J Microsc 228(Pt 3):366-372
  72. Jacobsen C (1999) Soft x-ray microscopy. Trends Cell Biol 9:44-47
  73. McKellar ARW (2010) High-resolution infrared spectroscopy with synchrotron sources. J Mol Spectrosc 262:1-10
  74. Ntziachristos V (2010) Going deeper than microscopy: the opti- cal imaging frontier in biology. Nat Meth 7(8):603
  75. Visible and Ultraviolet Spectroscopy, spectroscopynow.com/ coi/cda/detail
  76. Walsh MJ, German MJ, Singh M, Pollock HM, Hammiche A, Kyrgiou M, Stringfellow HF, Paraskevaidis E, Martin-Hirsch PL, Martin FL (2007) IR microspectroscopy: potential appli- cations in cervical cancer screening. Cancer Lett 246:1-11 References
  77. Savageau MA (1991) 20 years of S-systems. In: Voit EO (ed) Canonical nonlinear modeling: S-system approach to understand complexity. van Nostrand Reinhold, New York
  78. Voit EO (2000) Computational analysis of biochemical systems: a practical guide for biochemists and molecular biologists. Cambridge University Press, Cambridge References Harel-Sharvit L, Eldad N, Haimovich G, Barkai O, Duek L, Choder M (2010) RNA polymerase II subunits link transcrip- tion and mRNA decay to translation. Cell 143(4):552-563
  79. Preker P, Jensen TH (2010) Translation by remote control. Cell 143(4):501-502
  80. Stalk of RNAPII, Fig. 1 Multiple functions of the stalk-like structure (Rpb4/7) in RNAPII, (a) Structure of the PIC. The stalk-like structure comprising Rpb4 and Rpb7 (Rpb4/7) is located at a position close to the mRNA exit site of RNAPII. (b) The Rpb4/7 heterodimer is transferred from RNAPII to mRNA in the nucleus after which it regulates reactions in the cytoplasm such as export, translation, and degradation. The P-body (processing body) is a cellular compartment where mRNA is either degraded or stored in an inactive form References Fisher RA (1938) Indian Statistical congress. Cambridge University
  81. Higdon R et al (2013) Unraveling the complexities of life sci- ences data. Big Data J 1(1):BD17-23. http://www.liebertpub. com/overview/big-data/611/
  82. Holzman T, Kolker E (2003) Statistical analysis of global gene expression data: Some practical considerations. Curr Opin Biotechnol 15(1):52-57
  83. Kolker E, Stewart E, Ozdemir V (2012) Opportunities and chal- lenges for the life sciences community. OMICS: J Integrative Biol 16:138-147
  84. Werner E (2011a) On programs and genomes, arXiv:1110.5265v1 [q-bio.OT]. http://arxiv.org/abs/1110.5265
  85. Werner E (2011b) Cancer networks: a general theoretical and computational framework for understanding cancer, arXiv:1110.5865v1 [q-bio.MN]. http://arxiv.org/abs/1110\. 5865v1
  86. References Nowakowski J, Tinoco I Jr (1999) RNA structure in solution. In: Neidle S (ed) Oxford handbook of nucleic acid structure. Oxford Science, New York
  87. Yoshizawa S, Kawai G, Watanabe K, Miura K, Hirao I (1997) GNA trinucleotide loop sequences producing extraordinarily stable DNA minihairpins. Biochemistry 36:4761-4767
  88. Chou T, Lakatos G (2004) Clustered bottlenecks in mRNA translation and protein synthesis. Phys Rev Lett 93:1981011-1981014
  89. Gillespie DT (1977) Exact stochastic simulation of coupled chemical reactions. J Phys Chem 8:2340-2361
  90. Gingold H, Pilpel Y (2011) Determinants of translation effi- ciency and accuracy. Mol Syst Biol 7:481
  91. Kapp LD, Lorsch JR (2004) The molecular mechanics of eukary- otic translation. Annu Rev Biochem 73:657-704
  92. Kolomeisky AB (1998) Asymmetric simple exclusion model with local inhomogeneity. J Phys A Math Gen 31:1153-1164
  93. Krapivsky PL, Redner S, Ben-Naim E (2010) A kinetic view of statistical physics. Cambridge University Press, Cambridge
  94. Plotkin JB, Kudla G (2011) Synonymous but not the same: the causes and consequences of codon bias. Nat Rev Genet 12:32-42
  95. Romano MC, Thiel M, Stansfield I, Grebogi C (2009) Queueing phase transition: theory of translation. Phys Rev Lett 102:1981041-1981044
  96. Tian T, Burrage K (2003) Stochastic neural network models for gene regulatory networks. In: CEC 2003: the 2003 congress on evolutionary computation. Proceedings, Canberra, 8-12 Dec 2003. IEEE Computer Society, Piscataway, USA, pp 162-169
  97. Baras F, Malek-Mansour M, Pearson JE (1996) Microscopic simulation of chemical bistability in homogeneous systems. J Chem Phys 105:8257-8261
  98. Doi M, Edwards SF (1986) The theory of polymer dynamics. Clarendon Press, Oxford
  99. Fox RF (1978) Gaussian stochastic processes in physics. Phys Rep 48:180-283
  100. Gillespie DT (2002) The chemical Langevin and Fokker-Planck equations for the reversible isomerization reaction. J Phys Chem A 106:5063-5071
  101. Hanggi P, Grabert H, Talkner P, Thomas H (1984) Bistable systems: master equation versus Fokker-Planck modeling. Phys Rev A 29:371-378
  102. Knessel C, Mangel M, Matkowsky BJ, Schuss ZC (1984) Tier: solution of Kramers-Moyals equations for problems in chemical physics. J Chem Phys 81:1285-1293
  103. Kramers HA (1940) Brownian motion in a field of force and the diffusion model of chemical reactions. Physica 7:284-304
  104. Nicolis G, Lefever R (1977) Comment on the kinetic potential and the Maxwell construction in non-equilibrium chemical phase transitions. Phys Lett A 62:469
  105. Onsager L, Machlup S (1953) Fluctuatios and irreversible processes. Phys Rev 91:1505-1512
  106. Qian H (2006) Open-system nonequilibrium steady-state: statistical thermodynamics, fluctuations and chemical oscillations. J Phys Chem B 110:15063-15074 (Feature Article)
  107. Qian H (2011) Nonlinear stochastic dynamics of mesoscopic homogeneous biochemical reactions systems -An analytical theory. Nonlinearity 24:R19-R49 (Invited Article) References
  108. Gammaitoni L, H€ anggi P, Jung P, Marchesoni F (1998) Stochas- tic resonance. Rev Mod Phys 70(1):223-287
  109. Sague ´s F, Sancho JM, Garcı ´a-Ojalvo J (2007) Spatiotemporal order out of noise. Rev Mod Phys 79(3):829-882
  110. Chen L, Wang R, Li C, Aihara K (2010) Modeling biomolecular networks in cells: structures and dynamics. Springer, London
  111. Gibson MA, Bruck J (2000) Efficient exact stochastic simulation of chemical systems with many species and many channels. J Phys Chem A 104:1876-89
  112. Gillespie DT (1976) General method for numerically simulating stochastic time evolution of coupled chemical-reactions. J Comput Phys 22:403-434
  113. Gillespie DT (1977) Exact stochastic simulation of coupled chemical reactions. J Phys Chem 81:2340-2361
  114. Gillespie DT (2000) The chemical Langevin equation. J Chem Phys 113:297-305
  115. Gillespie DT (2001) Approximate accelerated stochastic simu- lation of chemically reacting systems. J Chem Phys 115:1716-33
  116. van Kampen NG (1981) Stochastic processes in physics and chemistry. Elsiever, Amsterdam
  117. Wilkinson DJ (2006) Stochastic modelling for systems biology. Chapman & Hall/CRC, Boca Raton
  118. Xu Z, Cai X (2008) Unbiased t-leap methods for stochastic simulation of chemically reacting systems. J Chem Phys 128:154112
  119. Palsson BO (2006) Systems biology: properties of reconstructed networks. Cambridge University Press, Cambridge Storey Tibshirani Method Winston Haynes Seattle Children's Research Institute, Seatlle, WA, USA References
  120. Apweiler R, Cornish-Bowden A, Hofmeyr J-HS, Kettner C, Leyh TS, Schomburg D, Tipton K (2005) The importance of uniformity in reporting protein-function data. TiBS 30(1):11-12
  121. Apweiler R, Armstrong R, Bairoch A, Cornish-Bowden A, Halling PJ, Hofmeyer J-HS, Kettner C, Leyh TS, Rohwer J, Schomburg D, Steinbeck C, Tipton K (2010) A large-scale protein-function database. Nat Chem Biol 6:785
  122. Kettner C, Hicks MG (2005) The dilemma of modern functional enzymology. Curr Enzyme Inhib 1:171-181
  123. Klipp E, Liebermeister R, Helbig A, Kowald A, Schaber J (2007) Systems biology standards -the community speaks. Nat Biotechnol 25:390-391
  124. LeNovere N, Courtot M, Laibe C (2007) Adding semantics in kinetic models of biochemical pathways. In: Hicks MG, Kettner C (eds) Proceedings of the 2nd international Beilstein symposium on ESCEC, Logos-Verlag, Berlin, pp 137-153
  125. Stelling J, Klamt S, Bettenbrock K, Schuster S, Gilles ED (2002) Metabolic network structure determines key aspects of functionality and regulation. Nature 420:190-193
  126. Taylor CF et al (2008) Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889-896
  127. Stroma Mary Helen Barcellos-Hoff Department of Radiation Oncology and Cell Biology, New York University School of Medicine, New York, NY, USA Synonyms Connective tissue; Microenvironment Definition Stroma is the non-parenchyma compartment in which vessels, nerves, and migratory immune and inflamma- tory cells reside. Stroma consists of mostly mesenchy- mal cells, such as fibroblasts, which produce the interstitial extracellular matrix (ECM), pericytes adja- cent to blood vessels, and adipocytes.
  128. Kratochwil K (1969) Organ specificity in mesenchymal induc- tion demonstrated in the embryonic development of the mammary gland of the mouse. Dev Biol 20:46-71
  129. Olumi AF, Grossfeld GD, Hayward SW, Carroll PR, Tlsty TD, Cunha GR (1999) Carcinoma-associated fibroblasts direct tumor progression of initiated human prostatic epithelium. Cancer Res 59(19):5002-5011
  130. Rowley DR (1998) What might a stromal response mean to prostate cancer progression? Cancer Metastasis Rev 17(4):411-419
  131. Sakakura T, Sakagami Y, Nishizuka Y (1982) Dual origin of mesenchymal tissues participating in mouse mammary gland embryogenesis. Dev Biol 91:202-207
  132. Bachmann J, Raue A, Schilling M, TimmerJ KU (2011) Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range. Mol Syst Biol 7(516). doi:10.1038/msb.2011.50
  133. Becker V, Schilling M, Bachmann J, Baumann U, Raue A, Maiwald T, Timmer J, Klingmueller U (2010) Covering a broad dynamic range: information processing at the erythropoietin receptor. Science 328(5984):1404-1408
  134. Meeker WQ, Escobar LA (1995) Teaching about approximate confidence regions based on maximum likelihood estima- tion. The Am Stat 49(1):48-53
  135. Murphy SA, van der Vaart AW (2000) On profile likelihood. J Am Stat Assoc 95(450):449-485
  136. Press WH, Teukolsky SLA, Flannery BNP, Vetterling WMT (1990) Numerical recipes: Fortran. Cambridge University Press, Cambridge
  137. Raue A, Kreutz C, Maiwald T, Bachmann J, Schilling M, Klingm€ uller U, Timmer J (2009) Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood. Bioinformatics 25(15):1923-1929
  138. Raue A, Becker V, Klingm€ uller U, Timmer J (2010) Identifiability and observability analysis for experimental design in non-linear dynamical models. Chaos 20(4):045105
  139. Seber GAF, Wild CJ (2003) Nonlinear regression. Wiley, New York
  140. Swameye I, M€ uller TG, Timmer J, Sandra O, Klingm€ uller U (2003) Identification of nucleocytoplasmic cycling as a remote sensor in cellular signaling by databased modeling. Proc Natl Acad Sci 100(3):1028-1033
  141. Walter E (1987) Identifiability of parametric models. Pergamon Press, New York References
  142. Khan JM, Tong JC, Ranganathan S (2009) Structural immunoin- formatics: understanding MHC-peptide-TR binding. In: Davies MN, Ranganathan S, Flower DR (eds) Bioinformatics for immunomics, vol 3, Immunomics reviews series. Springer, New York, pp 77-94
  143. Ruxton GD (2006) The unequal variance t-test is an underused alternative to Student's t-test and the Mann-Whitney U test. Behavior Ecol 17(2):688-690
  144. Sokal RR, Rohlf FJ (1995) Biometry: the principles and practice of statistics in biological research. W.H. Freeman, New York Zar JH (1999) Biostatistical analysis. Prentice Hall, Upper Sad- dle River, NJ References
  145. Barysenka A, Dress A, Schubert W (2009) An information- theoretical approach to medical image segmentation. In: ICISE'09 proceedings of the first IEEE international conference on information science and engineering. IEEE Computer Society, Washington, DC, pp 3592-3595
  146. Barysenka A, Dress A, Schubert W (2011) A comparative method for analysing toponome image stacks. East Asian J Appl Math 1:35-48
  147. Barysenka A, Dress A, Schubert W (2010) An information theoretic thresholding method for detecting protein colocalizations in stacks of fluorescence images. J Biotechnol 149:127-131
  148. Barysenka A. Copula-based methods of exploring statistical dependence between fluorescent markers, Ph.D. thesis, in preparation
  149. Dress A, Lokot T, Pustyl'nikov LD, Schubert W (2004) Poisson numbers and poisson distributions in subset surprisology. Ann Comb 8:473-485
  150. Schubert W (2002) Polymyositis, topological proteomics tech- nology and paradigm for cell invasion dynamics. J Theor Med 4:75-84
  151. Schubert W (2003) Topological proteomics, toponomics, MELK-technology. Adv Biochem Eng Biotechnol 83:189- 209, http://www.ncbi.nlm.nih.gov/pubmed/12934931
  152. Schubert W, Bonnekoh B, Pommer A, Philipsen L, B€ ockelmann R, Malykh Y, Gollnick H, Friedenberger M, Bode M, Dress A (2006) Analyzing proteome topology and function by automated multidimensional fluorescence microscopy. Nature Biotechnol 24:1270-1278
  153. Schubert W, Gieseler A, Krusche A, Hillert R (2009) Toponome mapping in prostate cancer: detection of 2000 cell surface protein clusters in a single tissue section and cell type specific annotation by using a three symbol code. J Proteome Res 8:2696-2707
  154. Wikipedia on Kullback-Leibler divergence. http://en.wikipedia. org/wiki/Kullback-Leibler_divergence Wikipedia on copula theory. http://en.wikipedia.org/wiki/ Copula_(statistics)
  155. Wikipedia on multi-spectral imaging. http://en.wikipedia.org/ wiki/Multi-spectral_image
  156. McLaughlin B, Bennett K (2011) Supervenience. In: Zalta EN (ed) The Stanford encyclopedia of philosophy. http:// plato.stanford.edu/archives/win2011/entries/supervenience/. Accessed on 15 Sep, 2012
  157. References Fleming TR, Harrington DP (1991) Counting processes and survival analysis. Wiley, New York
  158. Klein JP, Moeschberger ML (2010) Survival analysis: tech- niques for censored and truncated data. Springer, New York Kosorok MR (2009) Introduction to empirical processes and semiparametric inference. Springer, New York Lawless JF (2002) Statistical models and methods for lifetime data. Wiley, Hoboken
  159. Sun J (2009) The statistical analysis of interval-censored failure time data. Springer, New York Survival Curve Shuangge Ma Yale School of Public Health, Yale University, New Haven, CT, USA References
  160. Changeux JP, Danchin A (1976) Selective stabilization of devel- oping synapses as a mechanism for the specification of neuronal networks. Nature 264(5588):705-712
  161. Cheng D, Hoogenraad CC, Rush J, Ramm E, Schlager MA, Duong DM, Xu P, Wijayawardana SR, Hanfelt J, Nakagawa T, Sheng M, Peng J (2006) Relative and absolute quantification of postsynaptic density proteome isolated from rat forebrain and cerebellum. Mol Cell Proteomics 5(6):1158-1170
  162. Coughenour HD, Spaulding RS, Thompson CM (2004) The synaptic vesicle proteome: a comparative study in membrane protein identification. Proteomics 4(10):3141-3155
  163. Kandel ER, Schwartz JH (1982) Molecular biology of learning: modulation of transmitter release. Science 218(4571):433-443
  164. Peng J, Kim MJ, Cheng D, Duong DM, Gygi SP, Sheng MJ (2004) Semiquantitative proteomic analysis of rat forebrain postsynaptic density fractions by mass spectrometry. Biol Chem 279(20):21003-21011
  165. Pocklington AJ, Armstrong JD, Grant SGN (2006) Organization of brain-complexity-synapse proteome form and function. Brief Funct Genomic Proteomic 5:66-73
  166. Reddy PH, Manczak M, Mao P, Calkins MJ, Reddy AP, Shirendeb U (2010) Amyloid-beta and mitochondria in aging and Alzheimer's disease: implications for synaptic damage and cognitive decline. J Alzheimers Dis 20(Suppl 2):499-512
  167. S€ udhof TC, Rothman JE (2009) Membrane fusion: grappling with SNARE and SM proteins. Science 323(5913):474-477
  168. Xu W (2011) PSD-95-like membrane associated guanylate kinases (PSD-MAGUKs) and synaptic plasticity. Curr Opin Neurobiol 21(2):306-312
  169. Yoshimura Y, Yamauchi Y, Shinkawa T, Taoka M, Donai H, Takahashi N, Isobe T, Yamauchi T (2004) Molecular constituents of the postsynaptic density fraction revealed by proteomic analysis using multidimensional liquid chromatography-tandem mass spectrometry. J Neurochem 88(3):759-768
  170. Bode M, Irmler M, Friedenberger M, May C, Jung K, Stephan C, Meyer HE, Lach C, Hillert R, Krusche A, Beckers J, Marcus K, Schubert W (2008) Interlocking transcriptomics, proteomics and toponomics technologies for brain tissue analysis in murine hippocampus. Proteomics 8(6):1170-1178
  171. Schubert W (2003) Topological proteomics, toponomics, MELK-technology. Adv Biochem Eng Biotechnol 83:189-209
  172. Schubert W, Bonnekoh B, Pommer AJ, Philipsen L, Boeckelmann R, Maliykh J, Gollnick H, Friedenberger M, Bode M, Dress A (2006) Analyzing proteometopology and function by automated multidimensional fluorescence microscopy. Nat Biotechnol 24:1270-1278
  173. Schubert W, Gieseler A, Krusche A, Serocka P, Hillert R (2011) Next-generation biomarkers based on 100-parameter functional super-resolution microscopy TIS. N Biotechnol, doi: 10.1016/j.nbt.2011.12.004
  174. References Acebro ´n JA, Bonilla LL, Pe ´rez-Vicente CJ, Ritort F, Spigler R (2005) The Kuramoto model: a simple paradigm for synchronization phenomena. Mod Phys 77:137-185
  175. Arenas A, Dı ´az-Guilera A, Kurths J, Moreno Y, Zhou CS (2008) Synchronization in complex networks. Phys Rep 469:93-153
  176. Boccaletti A, Kurths J, Osipov G, Valladares DL, Zhou CS (2002) The synchronization of chaotic systems. Phys Rep 366:1-101
  177. Brown R, Kocarev L (2000) A unifying definition of synchroni- zation for dynamical systems. Chaos 10:344-349
  178. Danino T, Mondrago ´n-Palomino O, Tsimring L, Hasty J (2010) A synchronized quorum of genetic clocks. Nature 463:326-330
  179. Glass L (2001) Synchronization and rhythmic processes in physiology. Nature 410:277-284
  180. Nakao H, Arai K, Nagai K, Tsubo Y, Kuramoto Y (2005) Synchrony of limit-cycle oscillators induced by random external impulse. Phys Rev Lett 72:026220
  181. Wang JW, Zhang JJ, Yuan ZJ, Zhou TS (2007) Noise-induced switches in network systems of the genetic toggle switch. BMC Syst Biol 1:50
  182. Zhou TS, Chen L, Aihara K (2005) Molecular communication through stochastic synchronization induced by extracellular fluctuations. Phys Rev Lett 95:178103
  183. Zhou TS, Zhang JJ, Yuan ZJ, Xu AL (2007) External stimuli mediate collective rhythms: artificial control strategies. PLoS One 2:e231
  184. Pikovsky A, Rosenblum M, Kurths J (2001) Synchronization-a unified approach to nonlinear science. Cambridge University Press, Cambridge
  185. Wang JW, Zhang JJ, Yuan ZJ, Zhou TS (2007) Noise-induced switches in network systems of the genetic toggle switch. BMC Syst Biol 1:50
  186. Shmulevich I, Dougherty E, Kim S, Zhang W (2002) From Boolean to probabilistic boolean networks as models of genetic regulatory networks. Proceedings of the IEEE 90:1778-1792
  187. Syntactic Analysis ▶ Text Parsing Synthetic Biology, Predictability and Reliability Jinzhi Lei and Xiaojuan Sun Zhou Pei-Yuan Center for Applied Mathematics, Tsinghua University of Beijing, Beijing, China References
  188. Alon U (2005) An introduction to systems biology-design principles of biological circuits. CRC, Boca Raton Andranantoandro E, Basu S, Karig DK, Weiss R (2006) Syn- thetic biology: new engineering rules for an emerging disci- pline. Mol Syst Biol 2:2006.0028
  189. Artyukhin A, Wu L, Altschuler S (2009) Only two ways to achieve perfection. Cell 138:619-671
  190. Bardwell L, Zou X, Nie Q, Komarova N (2007) Mathematical models of specificity in cell signaling. Biophys J 92:3425-3441
  191. Kaneko K (2007) Evolution of robustness to noise and mutation in gene expression dynamics. PLoS One 2(5):e434
  192. Khalil AS, Collins JJ (2010) Synthetic biology: applications come of age. Nat Rev Genet 11:367-379
  193. Kitano H (2004) Biological robustness. Nat Rev Genet 5:826-837
  194. Komarova N, Zou X, Nie Q, Bardwell L (2005) A theoretical framework for specificity in cell signaling. Mol Syst Biol 1:2005.0023
  195. Ma W, Trusina A, El-Samad H, Lim W, Tang C (2009) Defining network topologies that can achieve biochemical adaptation. Cell 138:760-773
  196. Perez JC, Groisman EA (2009) Evolution of transcriptional regulatory circuits in bacteria. Cell 138:233-244
  197. An G, Mi Q, Dutta-Moscato J, Vodovotz Y (2009) Agent-based models in translational systems biology. Wiley Interdiscip Rev Syst Biol Med 1:159-171
  198. Fisher J, Henzinger TA (2007) Executable cell biology. Nat Biotechnol 25:1239-1249
  199. Fishman GS (2001) Discrete-event simulation: modeling, pro- gramming, and analysis. Springer, New York Hunt CA, Ropella GEP (2011) Moving beyond in silico tools to in silico science in support of drug development research. Drug Develop Res. doi:10.1002/ddr.20412, Published online: 16 Dec 2010
  200. Hunt CA, Ropella GE, Lam TN, Tang J, Kim SH, Engelberg JA, Sheikh-Bahaei S (2009) At the biological modeling and simulation frontier. Pharm Res 26:2369-2400
  201. Lam TN, Hunt CA (2009) Discovering plausible mechanistic details of hepatic drug interactions. Drug Metab Dispos 37:237-246
  202. Lam TN, Hunt CA (2010) Mechanistic insight from in silico pharmacokinetic experiments: roles of P-glycoprotein, Cyp3A4 enzymes, and microenvironments. J Pharmacol Exp Ther 332:398-412
  203. Park S, Kim SH, Ropella GE, Roberts MS, Hunt CA (2010) Trac- ing multiscale mechanisms of drug disposition in normal and diseased livers. J Pharmacol Exp Ther 334:124-136
  204. Ullah M, Wolkenhauer O (2010) Stochastic approaches in systems biology. Wiley Interdiscip Rev Syst Biol Med 2: m385-m397
  205. Yan L, Sheihk-Bahaei S, Park S, Ropella GE, Hunt CA (2008) Predictions of hepatic disposition properties using a mechanistically realistic, physiologically based model. Drug Metab Dispos 36:759-768
  206. Aldridge BB, Burke JM, Lauffenburger DA, Sorger PK (2006) Physicochemical modelling of cell signalling path- ways. Nat Cell Biol 8:1195-1203
  207. Alon U (2003) Biological networks: the tinkerer as an engineer. Science 301:1866-1867
  208. Chou I-C, Voit EO (2009) Recent developments in parameter estimation and structure identification of biochemical and genomic systems. Math Biosci 219:57-83
  209. Davies SP, Reddy H, Caivano M, Cohen P (2000) Specificity and mechanism of action of some commonly used protein kinase inhibitors. Biochem J 351:95-105
  210. Leung RK, Whittaker PA (2005) RNA interference: from gene silencing to gene-specific therapeutics. Pharmacol Ther 107:222-239
  211. Schoeberl B, Pace EA, Fitzgerald JB, Harms BD, Xu L, Nie L, Linggi B, Kalra A, Paragas V, Bukhalid R, Grantcharova V, Kohli N, West KA, Leszczyniecka M, Feldhaus MJ, Kudla AJ, Nielsen UB (2009) Therapeutically targeting ErbB3: a key node in ligand-induced activation of the ErbB receptor-PI3K axis. Sci Signal 2:ra31
  212. Voit EO (2000) Computational analysis of biochemical systems. A practical guide for biochemists and molecular biologists. Cambridge University Press, Cambridge, xii + 530 pp References
  213. Boran D, Iyengar R (2010) Systems approaches to polyphar- macology and drug discovery. Curr Opin Drug Discov Dev 13(3):297-309
  214. Butcher EC, Berg EL et al (2004) Systems biology in drug discovery. Nat Biotechnol 22(10):1253-1259
  215. Forst CV (2006) Host-pathogen systems biology. Drug Discov Today 11:220-227
  216. Glaab E, Baudot A et al (2012) EnrichNet: network-based gene set enrichment analysis. Bioinformatics 28(18): i451-i457
  217. Hood L, Perlmutter RM (2004) The impact of systems approaches on biological problems in drug discovery. Nat Biotechnol 22(10):1215-1217
  218. Ideker T, Krogan NJ (2012) Differential network biology. Mol Syst Biol 8:565
  219. Kitano H (2002) Systems biology: a brief overview. Science 295(5560):1662-1664
  220. Lee DS, Burd H et al (2009) Comparative genome-scale meta- bolic reconstruction and flux balance analysis of multiple Staphylococcus aureus genomes identify novel antimicrobial drug targets. J Bacteriol 191(12):4015-4024
  221. Orth JD, Thiele I et al (2010) What is flux balance analysis? Nat Biotechnol 28(3):245-248
  222. Raman K, Chandra N (2008) Mycobacterium tuberculosis interactome analysis unravels potential pathways to drug resistance. BMC Microbiology 2008(2):109
  223. Raman K, Yeturu K et al (2008) TargetTB: a target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis. BMC Syst Biol 2:109
  224. Rappuoli R, Aderem A (2011) A 2020 vision for vaccines against HIV, tuberculosis and malaria. Nature 473(7348):463-469 References
  225. Bornstein BJ, Keating SM, Jouraku A, Hucka M (2008) LibSBML: an API library for SBML. Bioinformatics 24:880-8801
  226. Demir E, Cary MP, Paley S, Fukuda K, Lemer C, Vastrik I et al (2010) The BioPAX community standard for pathway data sharing. Nat Biotechnol 28:935-942
  227. Dr€ ager A, Rodriguez N, Dumousseau M, D€ orr A, Wrzodek C, Le Nove `re N, Zell A, Hucka M (2011) JSBML: a flexible Java library for working with SBML. Bioinformatics 27:2167-2178
  228. Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC, Kitano H et al (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19:524-531
  229. Kovitz B (2004) MIME media type for the systems biology markup language (SBML). RFC 3823, Accessed June, 2011 http://www.rfc-editor.org/rfc/rfc3823.txt
  230. Le Nove `re N (2006) Model storage, exchange and integration. BMC Neurosci 7:S11-S11
  231. Le Nove `re N, Hucka M, Mi H, Moodie S, Schreiber F, Sorokin A et al (2009) The systems biology graphical nota- tion. Nat Biotechnol 27:735-741
  232. Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V et al (2010) BioModels database: an enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol 4:92
  233. Courtot M, Juty N, Knu ¨pfer C, Waltemath D, Zhukova A, Dra ¨ger A, Dumontier M, Finney A, Golebiewski M, Hastings J, Hoops S, Keating S, Kell DB, Kerrien S, Lawson J, Lister A, Lu J, Machne R, Mendes P, Pocock M, Rodriguez N, Villeger A, Wilkinson DJ, Wimalaratne S, Laibe C, Hucka M, Le Nove `re N (2011) Controlled vocabularies and seman- tics in systems biology. Mol Syst Biol 7:543
  234. Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceusters W, Goldberg LJ, Eilbeck K, Ireland A, Mungall CJ, Leontis N, The OBI Consortium, Rocca-Serra P, Ruttenberg A, Sansone S-A, Scheuermann RH, Shah N, Whetzel PL, Lewis S (2007) The OBO foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol 25:1251-1255
  235. Blinov ML, Ruebenacker O (2009) Integrating BioPAX pathway knowledge with SBML models. IET Syst Biol 3(5):317-328
  236. Blinov ML, Ruebenacker O, Moraru II (2008) Complexity and modularity of intracellular networks -a systematic approach for modeling and simulation. IET Syst Biol 2(5):363-368
  237. Blinov ML, Ruebenacker O, Schaff JC, Moraru II (2010) Model- ing without borders: creating and annotating VCell models using the web. Lect Notes Comput Sci, Vol 6053
  238. Ruebenacker Moraru II, Schaff JC, Blinov ML (2007) Kinetic modeling using BioPAX ontology. Proceedings of the IEEE international conference on bioinformatics and biomedicine, pp 339-348
  239. Systems Biology Resources Eduardo Mendoza Department of Computer Science, University of the Philippines Diliman, Quezon City, Philippines References EU FP7 (2010) Report on the workshop "from systems biology to systems medicine", Brussels
  240. Galperin MY, Cochrane GR (2011) The 2011 nucleic acids research database issue and the online molecular biology database collection. Nucleic Acids Research 19(Database Issue):D1-D6
  241. Gaudet P, Bairoch A, Field D, Sansone SA, Taylor C et al (2011) Towards BioDBCore: a community-defined informa- tion specification for biological databases. Nucleic Acids Research 19(Database Issue):D7-D10
  242. Hey T (2010) Data-driven scientific computing. In: Proceedings of the 10th international conference on systems biology, Edinburgh, 10-15 Oct 2010
  243. Kitano H (2002) Systems biology: a brief overview. Science 295:1663-1664
  244. Klipp E, Liebermeister W, Wierling C, Kowald A, Lehrach H, Herwig R (2009) Systems biology. A textbook. Wiley, Weinhei
  245. Li JWH, Vederas JC (2009) Drug discovery and natural products: end of an Era or an endless frontier? Science 325(10):161-165
  246. Markus F (2010) Bioinformatics and systems biology: collabo- rative research and resources. Springer, Berlin Mendoza ER (2009) Systems biology: its past, present and potential. Phil Sci Lett 2(1):16-34. http://www. philsciletters.org/ References
  247. Ansari HR, Flower DR, Raghava GP (2010) AntigenDB: an immunoinformatics database of pathogen antigens. Nucleic Acids Res 38:D847-D853
  248. Bhasin M, Raghava GP (2004) SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence. Bioinformatics 20:421-423
  249. Bhasin M, Raghava GPS (2006) A hybrid approach for predicting promiscuous MHC class I restricted T cell epi- topes. J Biosci 32:31-42
  250. Bonilla FA, Oettgen HC (2010) Adaptive immunity. J Allergy Clin Immunol 125(2 Suppl 2):S33-S40
  251. Boxus M, Willems L (2009) Mechanisms of HTLV-1 persis- tence and transformation. Br J Cancer 101:1497-1501
  252. Chavali AK, Gianchandani EP, Tung KS, Lawrence MB, Peirce SM, Papin JA (2008) Characterizing emergent properties of immunological systems with multi-cellular rule-based com- putational modeling. Trends Immunol 29:589-599
  253. Ehrenmann F, Kaas Q, Lefranc MP (2010) IMGT/3Dstructure- DB and IMGT/DomainGapAlign: a database and a tool for immunoglobulins or antibodies, T cell receptors, MHC. Nucleic Acids Res 38:D301-D307
  254. Forst CV (2006) Host-pathogen systems biology. Drug Discov Today 11:220-227
  255. Gowthaman U, Agrewala JN (2008) In silico tools for predicting peptides binding to HLA-class II molecules: more confusion than conclusion. J Proteome Res 7:154-163
  256. Janeway CA Jr, Medzhitov R (2002) Innate immune recognition. Annu Rev Immunol 20:197-216
  257. Lamkanfi M, Dixit VM (2010) Manipulation of host cell death pathways during microbial infections. Cell Host Microbe 8:44-54
  258. Meena LS, Rajni (2010) Survival mechanisms of pathogenic Mycobacterium tuberculosis H37Rv. FEBS J 277:2416-2427
  259. Moir S, Chun TW, Fauci AS (2010) Pathogenic mechanisms of HIV disease. Annu Rev Pathol 6:223-248, PMID: 21034222
  260. Pulendran B, Li S, Nakaya HI (2010) Systems vaccinology. Immunity 33:516-529
  261. Querec TD, Akondy RS, Lee EK, Cao W, Nakaya HI, Teuwen D, Pirani A, Gernert K, Deng J, Marzolf B, Kennedy K, Wu H, Bennouna S, Oluoch H, Miller J, Vencio RZ, Mulligan M, Aderem A, Ahmed R, Pulendran B (2009) Systems biology approach predicts immunogenicity of the yellow fever vaccine in humans. Nat Immunol 10:116-125
  262. Ramachandra L, Simmons D, Harding CV (2009) MHC mole- cules and microbial antigen processing in phagosomes. Curr Opin Immunol 21:98-104
  263. Rosenberg E (2005) The diversity of bacterial pathogenicity mechanisms. Genome Biol 6:320
  264. Saha S, Raghava GP (2006) Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Pro- teins 65(1):40-48
  265. Vita R, Zarebski L, Greenbaum JA, Emami H, Hoof I, Salimi N, Damle R, Sette A, Peters B (2010) The immune epitope database 2.0. Nucleic Acids Res 38:D854-D862
  266. Bandyopadhyay S, Kelley R, Ideker T (2006) Discovering reg- ulated networks during HIV-1 latency and reactivation. Pac Symp Biocomput 11:354-366
  267. Chuang HY, Lee E, Liu YT, Lee D, Ideker T (2007) Network- based classification of breast cancer metastasis. Mol Syst Biol 3:140-149
  268. Galitski T (2004) Molecular networks in model systems. Annu Rev Genomics Hum Genet 5:177-187
  269. Giri MS, Nebozhyn M, Showe L, Montaner LJ (2006) Microar- ray data on gene modulation by HIV-1 in immune cells: 2000-2006. J Leukoc Biol 80:1031-1043
  270. Ideker T, Sharan R (2008) Protein networks in disease. Genome Res 18:644-652
  271. Ideker T, Ozier O, Schwikowski B, Siegel AF (2002) Discover- ing regulatory and signalling circuits in molecular interaction networks. Bioinformatics 18(Suppl 1):S233-S240
  272. Kindt TJ, Goldsby RA, Osborne BA (2007) Immunology, 6th edn. W. H. Freeman, New York, pp 1-53
  273. Nathanson N, Rafi A et al (2007) Viral pathogenesis and immunity, 2nd edn. Academic Press, Amsterdam/Boston, pp 185-200
  274. Nibbe RK, Chance MR (2009) Approaches to biomarkers in human colorectal cancer: looking back, to go forward. Biomark Med 3:385-396
  275. Nibbe RK, Koyut€ urk M, Chance MR (2010) An integrative - omics approach to identify functional sub-networks in human colorectal cancer. PLoS Comput Biol 6:1-15
  276. Ptak RG, Fu W, Sanders-Beer BE, Dickerson JE, Pinney JW, Robertson DL, Rozanov MN, Katz KS, Maglott DR, Pruitt KD, Dieffenbach CW (2008) Cataloguing the HIV type 1 human protein interaction network. AIDS Res Hum Retrovi- ruses 24:1497-1502
  277. Sharan R, Ulitsky I, Shamir R (2007) Network-based prediction of protein function. Mol Syst Biol 88:1-13
  278. Tan SL, Ganji G, Paeper B, Proll S, Katze MG (2007) Systems biology and the host response to viral infection. Nat Biotechnol 25:1383-1389
  279. Bui HH, Sidney J, Peters B, Sathiamurthy M, Sinichi A, Purton KA, Mothe ´BR, Chisari FV, Watkins DI, Sette A (2005) Automated generation and evaluation of specific MHC bind- ing predictive tools: ARB matrix applications. Immunoge- netics 57(7):304-314
  280. Chaudhuri R, Ahmed S, Ansari FA, Singh HV, Ramachandran S (2008) MalVac: database of malarial vaccine candidates. Malar J 7:184
  281. Brusic V, Bajic VB, Petrovsky N (2004) Computational methods for prediction of T-cell epitopes -a framework for model- ling, testing, and applications. Methods 34:436-443
  282. Hackett CJ, Harn DA (eds) (2006) Vaccine adjuvants: immuno- logical and clinical principles. Humana Press, New Jersey Matzinger P (2007) Friendly and dangerous signals: is the tissue in control? Nat Immunol 8:11-13
  283. Petrovsky N, Aguilar JC (2004) Vaccine adjuvants: current state and future trends. Immunol Cell Biol 82:488-496
  284. Petrovsky N (2008) Freeing vaccine adjuvants from dangerous immunological dogma. Expert Rev Vaccin 7(1):7-10
  285. Singh M (ed) (2007) Vaccine adjuvants and delivery systems. Wiley, New York
  286. Vogel FR, Powell MF, Alving CR (eds) A compendium of vaccine adjuvants and excipients (2nd edn) Systems Medicine Gilles Clermont Center for Inflammation and Regenerative Modeling, University of Pittsburgh, Pittsburgh, PA, USA References
  287. An G, Hunt CA, Clermont G, Neugebauer E, Vodovotz Y (2007) Challenges and rewards on the road to translational systems biology in acute illness: four case reports from interdisciplin- ary teams. J Crit Care 22:169-175
  288. Clermont G, Auffray C, Moreau Y et al (2009) Bridging the gap between systems biology and medicine. Genome Med 1:88
  289. Kitano H (2002) Computational systems biology. Nature 420:206-210
  290. Kohn LT, Corrigan J, Donaldson MS (eds) (2000) To err is human: building a safer health system. National Academy Press, Washington, DC
  291. Leape LL, Berwick DM (2005) Five years after to err is human: what have we learned? JAMA 293:2384-2390
  292. Parker RS, Clermont G (2010) Systems engineering medicine: engineering the inflammation response to infectious and traumatic challenges. J R Soc Interface 7(48):989-1013
  293. Turnbaugh PJ, Ley RE, Hamady M, Fraser-Liggett CM, Knight R, Gordon JI (2007) The human microbiome project. Nature 449:804-810
  294. Faratian D, Goltsov A, Lebedeva G, Sorokin A, Moodie S, Mullen P, Kay C, Um IH, Langdon S, Goryanin I, Harrison DJ (2009) Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab. Cancer Res 69:6713-6720
  295. Saidi O, Cordon-Cardo C, Costa J (2007) Technology Insight: will systems pathology replace the pathologist? Nat Rev Urol 4:39-45
  296. El-Hamamsy I, Yacoub MH (2009) Cellular and molecular mechanisms of thoracic aortic aneurysms. Nat Rev Cardiol 6(12):771-786. doi:10.1038/nrcardio.2009.191, Nature Pub- lishing Group
  297. Hoppensteadt FC, Peskin CS (2010) Modeling and simulation in medicine and the life sciences. Texts in applied mathematics. Springer, New York, p 376. Retrieved from http://www. amazon.com/Modeling-Simulation-Medicine-Sciences- Mathematics/dp/1441928715
  298. Pearson TA, Manolio TA (2008) How to interpret a genome-wide association study. J Am Med Assoc 299(11):1335-1344. doi:10.1001/jama.299.11.1335
  299. Pimienta G, Chaerkady R, Pandey A (2009) Phospho-proteomics. In: de Graauw M (ed) Methods 527: 107-116. Humana Press, Totowa. doi:10.1007/978-1-60327-834-8
  300. West DB (2000) Introduction to graph theory, 2nd edn. Prentice Hall, Upper Saddle River, p 470. Retrieved from http://www. amazon.com/Introduction-Graph-Theory-Douglas-West/dp/ 0130144002
  301. Wist AD, Berger SI, Iyengar R (2009) Systems pharmacology and genome medicine: a future perspective. Genome Medicine 1(1):11. doi:10.1186/gm11
  302. Zhu Z, Cuozzo J (2009) Review article: high-throughput affin- ity-based technologies for small-molecule drug discovery. Journal of Biomolecular Screening 14(10):1157-1164. doi:10.1177/1087057109350114
  303. Amberger J, Bocchini CA, Scott AF, Hamosh A (2009) McKusick's online Mendelian inheritance in man (OMIM). Nucleic Acids Res 37:D793-D796
  304. Goh KI, Cusick ME, Valle D, Childs B, Vidal M, Baraba ´si AL (2007) The human disease network. Proc Natl Acad Sci USA 104:8685-8690
  305. Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M (2010) KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res 38:D355-D360
  306. Nacher JC, Schwartz JM (2008) A global view of drug-therapy interactions. BMC Pharmacol 8:5
  307. Osborne J, Flatow J, Holko M, Lin S, Kibbe W, Zhu L, Danila MI, Feng G, Chisholm RL (2009) Annotating the human genome with Disease Ontology. BMC Genomics 10:S6
  308. Paolini GV, Shapland RHB, van Hoorn WP, Mason JS, Hopkins AL (2006) Global mapping of pharmacological space. Nat Biotechnol 24:805-815
  309. Spiro Z, Kovacs IA, Csermely P (2008) Drug-therapy networks and the prediction of novel drug targets. J Biol 7:20 WHO Collaborating Centre for Drug Statistics Methodology (2010) ATC classification index with DDDs, Oslo, Norway
  310. Wishart DS, Knox C, Guo AC, Cheng D, Shrivastava S, Tzur D, Gautam B, Hassanali M (2008) DrugBank: a knowledgebase of drugs, drug actions and drug targets. Nucleic Acids Res 36:D901-D906
  311. Systems Pharmacology, Drug-Target Networks References
  312. Berger SI, Iyengar R (2009) Network analyses in systems phar- macology. Bioinformatics 25:2466-2472
  313. Dalkic E, Wang X, Wright W, Chan C (2010) Cancer-drugs associations: a complex system. PLoS One 5:e10031
  314. Goh KI, Cusick ME, Valle D, Childs B, Vidal M, Baraba ´si AL (2007) The human disease network. Proc Natl Acad Sci USA 104:8685-8690
  315. Hopkins AL (2008) Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol 4:682-690
  316. Ma'ayan A, Jenkins SL, Goldfarb J, Iyengar R (2007) Network analysis of FDA approved drugs and their targets. Mt Sinai J Med 74:27-32
  317. Nacher JC, Schwartz JM (2008) A global view of drug-therapy interactions. BMC Pharmacol 8:5
  318. Schwartz JM, Nacher JC (2009) Local and global modes of drug action in biochemical networks. BMC Chem Biol 9:4
  319. Shiwen Z, Li S (2010) Network-based relating pharmacological and genomic spaces for drug target identification. PLoS One 5:e11764
  320. Spiro Z, Kovacs IA, Csermely P (2008) Drug therapy networks and the prediction of novel drug targets. J Biol 7:20
  321. Yıldırım MA, Goh KI, Cusick ME, Baraba ´si AL, Vidal M (2007) Drug-target network. Nat Biotechnol 25:1119-1126
  322. Clermont G, Auffray C, Moreau Y, Rocke DM, Dalevi D, Dubhashi D, Marshall DR, Raasch P, Dehne F, Provero P, Tegner J, Aronow BJ, Langston MA, Benson M (2009) Bridging the gap between systems biology and medicine. Genome Med 1:88.1-88.3
  323. Kitano H (2002) Systems biology: a brief overview. Science 295:1662-1664
  324. Peng X, Chan EY, Li Y, Diamond DL, Korth MJ, Katze MG (2009) Virus-host interactions: from systems biology to translational research. Curr Opin Microbiol 12:432-438
  325. Tan S, Ganji G, Paeper B, Proll S, Katze MG (2007) Systems biology and the host response to viral infection. Nat Biotechnol 25:1383-1389
  326. Systems, Autopoietic Leonardo Bich and Arantza Etxeberria Department of Logic and Philosophy of Science, IAS-Research Center for Life, Mind, and Society, University of the Basque Country, UPV/EHU, Donostia-San Sebastia ´n, Spain References
  327. Boogerd FC, Bruggerman FJ, Hofmeyr J-HS, Westerhoff HV (eds) (2007) Systems biology. Philosophical foundations. Elsevier, Amsterdam
  328. Di Paolo EA (2004) Special issue on: unbinding biological autonomy: Francisco Varela's contributions to artificial life. Artificial Life 10:231-360
  329. Letelier J-C, Soto-Andrade J, Guinez-Abarzua F, Cardenas M-L, Cornish-Bowden A (2006) Organizational invariance and metabolic closure: analysis in terms of (M, R) systems. Journal of Theoretical Biology 238:949-961
  330. Luisi PL (2006) The emergence of life. From chemical origins to synthetic biology. Cambridge University Press, New York
  331. Maturana M, Varela F (1973/1980) De ma ´quinas y seres vivos. Autopoiesis: La organizacio ´n de lo vivo. Editorial Universitaria, Santiago. (English translation: Autopoiesis and cognition. The realization of the living. Reidel, Boston)
  332. Maturana H, Varela F (1984/1987) El a ´rbol del conocimiento. Editorial Universitaria, Santiago de Chile. (English translation: The tree of knowledge. Shambhala, Boston)
  333. Varela F (1979) Principles of biological autonomy. Elsevier North Holland, New York
  334. Varela F, Maturana H, Uribe R (1974) Autopoiesis: the organi- zation of living systems, its characterization and a model. Biosystems 5:187-196
  335. Varela F, Thompson E, Rosch E (1991) The embodied mind. Cognitive science and human experience. MIT Press, Cambridge, MA
  336. Weber A, Varela FJ (2002) Life after kant: natural purposes and the autopoietic foundations of biological indi- viduality. Phenomenology and the Cognitive Sciences 1(2):97-125