Biological Theory

, Volume 10, Issue 1, pp 18–35 | Cite as

Explanatory Integration Challenges in Evolutionary Systems Biology

Thematic Section Article: Evolutionary Systems Biology


Evolutionary systems biology (ESB) aims to integrate methods from systems biology and evolutionary biology to go beyond the current limitations in both fields. This article clarifies some conceptual difficulties of this integration project, and shows how they can be overcome. The main challenge we consider involves the integration of evolutionary biology with developmental dynamics, illustrated with two examples. First, we examine historical tensions between efforts to define general evolutionary principles and articulation of detailed mechanistic explanations of specific traits. Next, these tensions are further clarified by considering a recent case from another field focused on developmental dynamics: stem cell biology. In the stem cell case, incompatible explanatory aims block integration. Experimental approaches aim at mechanistic explanation while dynamical system models offer explanation in terms of general principles. We then discuss an ESB case in which integration succeeds: search for general attractors using a dynamical systems framework synergizes with the experimental search for detailed mechanisms. Contrasts between the positive and negative cases suggest general lessons for achieving an integrated understanding of developmental and evolutionary dynamics. The key integrative move is to acknowledge two complementary aims, both relevant to explanation: identifying the space of possible dynamic states and trajectories, and mechanistic understanding of causal interactions underlying a specific phenomenon of interest. These two aims can support one another in a joint project characterizing dynamic aspects of evolving lineages. This more inclusive project can lead to insights that cannot be reached by either approach in isolation.


Covering laws Developmental biology Dynamical systems theory (DST) Evolutionary systems biology (ESB) Level of explanation Mechanism Stem cells 



We would like to thank Orkun Soyer, Maureen O’Malley, and Sabina Leonelli for organizing the workshop on ESB and the KLI for hosting this event. We are grateful to the participants of the workshop for many fruitful discussions, and to Gerd Müller and Werner Callebaut for taking the initiative to have a thematic section based on important themes discussed at the workshop. Johannes Jaeger would like to thank Karl Wotton for the hedgehog and the fox, as well as Nick Monk and the late Brian Goodwin for countless inspiring discussions on the philosophy of science. Sara Green acknowledges support from The Danish Research Council for Independent Research/Humanities for funding to the project Philosophy of Contemporary Science in Practice. Melinda Fagan’s research on this paper was supported by the Mosle Foundation and a Faculty Innovation Fellowship from the Humanities Research Center at Rice University. Johannes Jaeger’s research group is supported by the MEC-EMBL agreement for the CRG/EMBL Research Unit in Systems Biology.


  1. Alberch P (1991) From genes to phenotype: dynamical systems and evolvability. Genetica 84:5–11CrossRefGoogle Scholar
  2. Alon U (2007) An introduction to systems biology: design principles of biological circuits. Chapman and Hall, Boca RatonGoogle Scholar
  3. Amundson R (1994) Two concepts of constraint: adaptationism and the challenge from developmental biology. Philos Sci 61:556–578CrossRefGoogle Scholar
  4. Amundson R (2001) Adaptation and development: on the lack of common ground. In: Orzack SH, Sober E (eds) Adaptationism and optimality. Cambridge University Press, Cambridge, pp 303–334CrossRefGoogle Scholar
  5. Ashyraliyev M, Fomekong-Nanfack Y, Kaandorp JA et al (2009) Systems biology: parameter estimation for biochemical models. FEBS J 276:886–902CrossRefGoogle Scholar
  6. Banga JR (2008) Optimization in computational systems biology. BMC Syst Biol 2:47CrossRefGoogle Scholar
  7. Beatty J (1995) The evolutionary contingency thesis. In: Wolters G, Bechtel W, Richardson RC (1993) Discovering complexity: decomposition and localization as strategies in scientific research. Princeton University Press, PrincetonGoogle Scholar
  8. Bechtel W, Richardson R (1993) Discovering complexity: decomposition and localization as strategies in scientific research. Princeton University Press, Princeton, New JerseyGoogle Scholar
  9. Berlin I (1953) The hedgehog and the fox: an essay on Tolstoy’s view on history. Weidenfeld & Nicolson, LondonGoogle Scholar
  10. Burian RM, Richardson RC (1990) Form and order in evolutionary biology: Stuart Kauffman’s transformation of theoretical biology. PSA 2:267–287Google Scholar
  11. Cain CJ, Conte DA, García-Ojeda ME et al (2008) What systems biology is (not, yet). Science 320:1013–1014CrossRefGoogle Scholar
  12. Carroll RL (2000) Towards a new evolutionary synthesis. Trends Ecol Evol 15:27–32CrossRefGoogle Scholar
  13. Collins JP, Gilbert S, Laubichler MD, Müller GB (2007) Modeling in EvoDevo: how to integrate development, evolution, and ecology. In: Laubichler MD, Müller GB (eds) Modeling biology: structures, behaviors, evolution. MIT Press, Cambridge, pp 355–378Google Scholar
  14. Craver C (2007) Explaining the brain: mechanisms and the mosaic unity of neuroscience. Clarendon, OxfordCrossRefGoogle Scholar
  15. Csete M, Doyle J (2002) Reverse engineering biological complexity. Science 295:1664–1669CrossRefGoogle Scholar
  16. Darwin C (1859) On the origin of species by means of natural selection. John Murray, LondonGoogle Scholar
  17. Dawkins R (1976) The selfish gene. Oxford University Press, OxfordGoogle Scholar
  18. De Vries H (1940) Species and varieties: their origin by mutation. Open Court, ChicagoGoogle Scholar
  19. Delbrück M (1949) Discussion. In Unités biologiques douées de continuité génétique. Editions du Centre National de la Recherche Scientifique, ParisGoogle Scholar
  20. Depew DJ, Weber BH (1995) Darwinism evolving: systems dynamics and the genealogy of natural selection. MIT Press, Cambridge, MAGoogle Scholar
  21. Enver T, Pera M, Peterson C, Andrews PW (2009) Stem cell states, fates, and the rules of attraction. Cell Stem Cell 4:387–397CrossRefGoogle Scholar
  22. Espinosa-Soto C, Martin OC, Wagner A (2011) Phenotypic plasticity can facilitate adaptive evolution in gene regulatory circuits. BMC Evol Biol 11:5CrossRefGoogle Scholar
  23. Fagan MB (2012) Waddington redux: models and explanation in stem cell and systems biology. Biol Philos 27:179–213CrossRefGoogle Scholar
  24. Felix M-A (2012) Evolution in developmental phenotype space. Curr Opin Genet Dev 22:593–599CrossRefGoogle Scholar
  25. François P (2012) Evolution in silico: from network structure to bifurcation theory. In: Soyer S (ed) Evolutionary systems biology. Springer, New York, pp 157–182CrossRefGoogle Scholar
  26. Furusawa C, Kaneko K (2012) A dynamical-systems view of stem cell biology. Science 338:215–217CrossRefGoogle Scholar
  27. Glennan S (1996) Mechanisms and the nature of causation. Erkenntnis 44:49–71CrossRefGoogle Scholar
  28. Goodwin B (1982) Development and evolution. J Theor Biol 97:43–55CrossRefGoogle Scholar
  29. Goodwin B (1994) How the leopard changed its spots: the evolution of complexity. Phoenix, LondonGoogle Scholar
  30. Goodwin B (2009) Beyond the Darwinian paradigm: understanding biological forms. In: Ruse M, Travis J (eds) Evolution: the first four billion years. Harvard University Press, Cambridge, MA, pp 299–312Google Scholar
  31. Goodwin B, Kauffman S, Murray JD (1993) Is morphogenesis an intrinsically robust process? J Theor Biol 163:135–144CrossRefGoogle Scholar
  32. Gould SJ (1989) Wonderful life. Norton, New YorkGoogle Scholar
  33. Griffiths PE (1996) The historical turn in the study of adaptation. Brit J Phil Sci 47:511–532CrossRefGoogle Scholar
  34. Haag ES (2007) Compensatory vs. pseudocompensatory evolution in molecular and developmental interactions. Genetica 129:45–55CrossRefGoogle Scholar
  35. Hempel CG, Oppenheim P (1948) Studies in the logic of explanation. Philos Sci 15:135–175CrossRefGoogle Scholar
  36. Hochedlinger K, Plath K (2009) Epigenetic reprogramming and induced pluripotency. Development 136:509–523CrossRefGoogle Scholar
  37. Hogeweg P (2012) Toward a theory of multilevel evolution: long-term information integration shapes the mutational landscape and enhances evolvability. In: Soyer O (ed) Evolutionary systems biology. Springer, London, pp 195–223CrossRefGoogle Scholar
  38. Huang S (2009a) Non-genetic heterogeneity of cells in development: more than just noise. Development 136:3853–3862CrossRefGoogle Scholar
  39. Huang S (2009b) Reprogramming cell fates: reconciling rarity with robustness. BioEssays 31:546–560CrossRefGoogle Scholar
  40. Huang S (2011a) Systems biology of stem cells: three useful perspectives to help overcome the paradigm of linear pathways. Phil Trans R Soc B 366:2247–2259CrossRefGoogle Scholar
  41. Huang S (2011b) The molecular and mathematical basis of Waddington’s epigenetic landscape: a framework for post-Darwinian biology? BioEssays 34:149–157CrossRefGoogle Scholar
  42. Huang S, Ernberg I, Kauffman S (2009) Cancer attractors: a systems view of tumors from a gene network dynamics and developmental perspective. Semin Cell Dev Biol 20:869–876CrossRefGoogle Scholar
  43. Jaeger J (2011) The gap gene network. Cell Mol Life Sci 68:243–274CrossRefGoogle Scholar
  44. Jaeger J, Crombach A (2012) Life’s attractors: understanding developmental systems through reverse engineering and in silico evolution. In: Soyer O (ed) Evolutionary systems biology. Springer, London, pp 93–119CrossRefGoogle Scholar
  45. Jaeger J, Monk N (2010) Reverse engineering of gene regulatory networks. In: Lawrence ND, Girolami M, Rattray M et al (eds) Learning and inference in computational systems biology. MIT Press, Cambridge, MA, pp 9–34Google Scholar
  46. Jaeger J, Monk N (2013) Keeping the gene it its place. In: Lambert D, Chetland C, Millar C (eds) The intuitive way of knowing: a tribute to Brian Goodwin. Floris Books, Glasgow, pp 153–189Google Scholar
  47. Jaeger J, Monk N (2014) Bioattractors: dynamical systems theory and the evolution of regulatory processes. J Physiol 592:2267CrossRefGoogle Scholar
  48. Jaeger J, Sharpe J (2014) On the concept of mechanism in development. In: Minelli A, Pradeu T (eds) Towards a theory of development. Oxford University Press, Oxford, pp 56–78CrossRefGoogle Scholar
  49. Jaeger J, Surkova S, Blagov M et al (2004a) Dynamic control of positional information in the early Drosophila embryo. Nature 430:368–371CrossRefGoogle Scholar
  50. Jaeger J, Blagov M, Kosman D et al (2004b) Dynamical analysis of regulatory interactions in the gap gene system of Drosophila melanogaster. Genetics 167:1721–1737CrossRefGoogle Scholar
  51. Jaeger J, Irons D, Monk N (2012) The inheritance of process: a dynamical systems approach. J Exp Zool B 318:591–612CrossRefGoogle Scholar
  52. Kaneko K (2011) Characterization of stem cells and cancer cells on the basis of gene expression profile stability, plasticity, and robustness. BioEssays 33:403–413CrossRefGoogle Scholar
  53. Kaplan DM, Craver CF (2011) The explanatory force of dynamical and mathematical models in neuroscience: a mechanistic perspective. Philos Sci 78:601–627CrossRefGoogle Scholar
  54. Kauffman S (1969) Metabolic stability and epigenesis in randomly constructed genetic nets. J Theor Biol 22:437–467CrossRefGoogle Scholar
  55. Kauffman S (1970) Articulation of parts explanation in biology and the rational search for them. Proceedings of the Biennial Meeting of the Philosophy of Science Association, PSA, pp 257–272Google Scholar
  56. Kauffman S (1993) Origins of order in evolution: self-organisation and selection. Oxford University Press, New YorkGoogle Scholar
  57. Kauffman S (1995) At home in the universe: the search for laws of self-organization and complexity. Oxford University Press, New YorkGoogle Scholar
  58. Kimura M (1985) The neutral theory of molecular evolution. Cambridge University Press, CambridgeGoogle Scholar
  59. Knight CG, Pinney JW (2009) Making the right connections: biological networks in the light of evolution. BioEssays 10:1080–1090CrossRefGoogle Scholar
  60. Koonin EV (2011) Are there laws of genome evolution? PLoS Comput Biol 7:e1002173CrossRefGoogle Scholar
  61. Koonin EV, Wolf YI (2010) Constraints and plasticity in genome and molecular-phenome evolution. Nat Rev Genet 11:487–498CrossRefGoogle Scholar
  62. Krakauer D, Collins JP, Erwin D et al (2011) The challenges and scope of theoretical biology. J Theor Biol 276:269–276CrossRefGoogle Scholar
  63. Lu R, Markowetz F, Unwin RD et al (2009) Systems-level dynamic analyses of fate change in murine embryonic stem cells. Nature 462:358–362CrossRefGoogle Scholar
  64. Lynch M (2007a) The evolution of genetic networks by non-adaptive processes. Nat Rev Genet 8:803–813CrossRefGoogle Scholar
  65. Lynch M (2007b) The frailty of adaptive hypotheses for the origins of organismal complexity. Proc Natl Acad Sci USA 104:8597–8604CrossRefGoogle Scholar
  66. MacArthur BD, Ma’ayan A, Lemischka IR (2009) Systems biology of stem cell fate and cellular reprogramming. Nat Rev Mol Cell Biol 10:672–681Google Scholar
  67. Machamer P, Darden L, Craver C (2000) Thinking about mechanisms. Philos Sci 67:1–25CrossRefGoogle Scholar
  68. MacLeod M, Nersessian N (2013) Coupling simulation and experiment: the bimodal strategy in integrative systems biology. Stud Hist Phil Biol Biomed Sci 44:572–584CrossRefGoogle Scholar
  69. Manu SS, Spirov AV, Gursky VV et al (2009a) Canalization of gene expression in the Drosophila blastoderm by gap gene cross regulation. PLoS Biol 7:e1000049CrossRefGoogle Scholar
  70. Manu SS, Spirov AV, Gursky VV et al (2009b) Canalization of gene expression and domain shifts in the Drosophila blastoderm by dynamical attractors. PLoS Comput Biol 5:e1000303CrossRefGoogle Scholar
  71. Mayr E (1983) How to carry out the adaptationist program? Am Nat 121:324–334CrossRefGoogle Scholar
  72. Mayr E (2005) What makes biology unique? Considerations on the autonomy of a scientific discipline. Cambridge University Press, CambridgeGoogle Scholar
  73. Melton D, Cowan C (2009) Stemness: definitions, criteria, and standards. In: Lanza R, Gearhart J, Hogan B et al (eds) Essentials of stem cell biology. Academic Press, San Diego, pp xxii–xxixGoogle Scholar
  74. Mjolsness E, Sharp DH, Reinitz J (1991) A connectionist model of development. J Theor Biol 152:429–453CrossRefGoogle Scholar
  75. Newman SA (1993) Is segmentation generic? BioEssays 15:277–283CrossRefGoogle Scholar
  76. Newman SA (1994) Generic physical mechanisms of tissue morphogenesis: a common basis for development and evolution. J Evol Biol 7:467–488CrossRefGoogle Scholar
  77. O’Malley M (2012) Evolutionary systems biology: historical and philosophical perspectives on an emerging synthesis. In: Soyer O (ed) Evolutionary systems biology. Springer, London, pp 1–28CrossRefGoogle Scholar
  78. Oster G, Alberch P (1982) Evolution and bifurcation of developmental programs. Evolution 36:444–459CrossRefGoogle Scholar
  79. Papp B, Notebaart RA, Pál C (2011) Systems-biology approaches for predicting genomic evolution. Nat Rev Genet 12:591–602CrossRefGoogle Scholar
  80. Pigliucci M (2009) An extended synthesis for evolutionary biology. Ann NY Acad Sci 1168:218–228CrossRefGoogle Scholar
  81. Pigliucci M (2010) Genotype-phenotype mapping and the end of the “genes as blueprint” metaphor. Phil Trans R Soc Lond B 365:557–566CrossRefGoogle Scholar
  82. Pigliucci M, Müller GB (eds) (2010) Evolution: the extended synthesis. MIT Press, Cambridge, MAGoogle Scholar
  83. Ramalho-Santos M, Willenbring H (2007) On the origin of the term “stem cell”. Cell Stem Cell 1:35–38CrossRefGoogle Scholar
  84. Reinitz J, Sharp DH (1995) Mechanism of eve stripe formation. Mech Dev 49:133–158CrossRefGoogle Scholar
  85. Richardson R (2001) Complexity, self-organization and selection. Biol Philos 16:653–682CrossRefGoogle Scholar
  86. Riedl R (1978) Order in living organisms: a systems analysis of evolution. Wiley, ChichesterGoogle Scholar
  87. Salazar-Ciudad I (2006) On the origins of morphological disparity and its diverse developmental bases. BioEssays 28:1112–1122CrossRefGoogle Scholar
  88. Salmon W (1989) Four decades of scientific explanation. University of Minnesota Press, MinneapolisGoogle Scholar
  89. Smith KC (1992) Neo-rationalism versus neo-Darwinism: integrating development and evolution. Biol Philos 7:431–451CrossRefGoogle Scholar
  90. Soldner F, Jaenisch R (2012) iPSC disease modeling. Science 338:1155–1156CrossRefGoogle Scholar
  91. Steinacher A, Soyer O (2012) Evolutionary principles underlying structure and response dynamics of cellular networks. In: Soyer O (ed) Evolutionary systems biology. Springer, London, pp 225–247CrossRefGoogle Scholar
  92. Strogatz SH (2000) Nonlinear dynamics and chaos. With applications to physics, biology, chemistry and engineering. Perseus Books, New YorkGoogle Scholar
  93. Tachibana M, Amato P, Sparman M et al (2013) Human embryonic stem cells derived by somatic cell nuclear transfer. Cell 153:1–11CrossRefGoogle Scholar
  94. Thom R (1976) Structural stability and morphogenesis. Benjamin, ReadingGoogle Scholar
  95. True J, Haag ES (2001) Developmental system drift and flexibility in evolutionary trajectories. Evol Dev 3:109–119CrossRefGoogle Scholar
  96. van den Berg, Debbie LC, Snoek T et al (2010) An Oct4-centered protein interaction network in embryonic stem cells. Cell Stem Cell 6:369–381CrossRefGoogle Scholar
  97. Waddington CH (1940) Organisers and genes. Cambridge University Press, CambridgeGoogle Scholar
  98. Waddington CH (1957) The strategy of the genes. Taylor and Francis, LondonGoogle Scholar
  99. Wagner A (2008) Gene duplications, robustness and evolutionary innovations. BioEssays 30:367–373CrossRefGoogle Scholar
  100. Wagner A (2011a) Genotype networks shed light on evolutionary constraints. Trends Ecol Evol 26:577–584CrossRefGoogle Scholar
  101. Wagner A (2011b) The origins of evolutionary innovations: a theory of transformative change in living systems. Oxford University Press, New YorkCrossRefGoogle Scholar
  102. Wagner A (2011c) The molecular origins of evolutionary innovations. Trends Genet 27:397–410CrossRefGoogle Scholar
  103. Webster G, Goodwin B (1996) Form and transformation: generative and relational principles in biology. Cambridge University Press, CambridgeGoogle Scholar
  104. Yamanaka S (2009) Elite and stochastic models for induced pluripotent stem cell generation. Nature 460:49–52CrossRefGoogle Scholar
  105. Zenobi R (2013) Single-cell metabolomics: analytical and biological perspectives. Science 342:124325CrossRefGoogle Scholar
  106. Zhou JX, Huang S (2011) Understanding gene circuits at cell-fates branch points for rational cell reprogramming. Trends Genet 27:55–62CrossRefGoogle Scholar
  107. Zhou Q, Melton DA (2008) Extreme makeover: converting one cell into another. Cell Stem Cell 3:382–388CrossRefGoogle Scholar

Copyright information

© Konrad Lorenz Institute for Evolution and Cognition Research 2014

Authors and Affiliations

  1. 1.Centre for Science Studies, Department of Physics and AstronomyAarhus UniversityAarhusDenmark
  2. 2.Department of PhilosophyUniversity of UtahSalt Lake CityUSA
  3. 3.EMBL/CRG Research Unit in Systems BiologyCentre de Regulació Genòmica (CRG)BarcelonaSpain
  4. 4.Universitat Pompeu Fabra (UPF)BarcelonaSpain

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