Nothing in biology makes sense
except when properly quantified in the light of evolution.
Evolutionary systems biology aims to bring together the rich mechanistic details of current systems biology and the long-standing quantitative experience in evolutionary genetics in order to increase the quantitative rigor of biological analyses. For a short introduction, see here, and for a more through introduction and a more rigorous defintion of EvoSysBio, see here.
Since current systems biology means many things to many people, it is perhaps inevitable that evolutionary systems biology might be even broader. We hope that EvoSysBio will bring together approaches from systems biology and evolutionary biology to help construct more realistic and illuminating models of life and its evolution. This goes beyond comparative analyses and aims to provide mechanistic models reliable enough to predict evolution. Weather forecasts are very difficult, yet computer models have helped tremendously. Will we be able to simulate key aspects of evolution in a similar way?
Such questions and related issues are regularly discussed at diverse Meeting on Evolutionary Systems Biology:
Upcoming meetings that focus on EvoSysBio:
2017 SMBE Symposium
"Evolutionary Systems Biology of Cells",
3rd of July during the SMBE Conference
July, 2nd - 6th, 2017, Austin Texas, USA.
More on the Symposium Website
Other symposia at the 2017 SMBE conference
also contribute towards progress in addressing
important and broad challenges in EvoSysBio
as defined here.
The last meeting was:
Thur + Fri, Aug 4-5, 2016 at UW-Madison
Workshop on Evolutionary Systems Biology & Modeling, Madison, Wisconsin, USA, Website
Soyer O.S. (editor, 2012). Evolutionary Systems Biology. Book series: Advances in Experimental Medicine and Biology. Springer. Contents
Loewe L (2009) A framework for evolutionary systems biology. BMC Systems Biology 3:27;
Framework redefined: Loewe (2016) Systems in Evolutionary Systems Biology, pp 297–318, vol 4 in: Kliman (ed) Encyclopedia of Evolutionary Biology, Academic Press, Oxford, UK. Summarized in 10 slides on Figshare.
Ibarra, R. U., Edwards, J. S., & Palsson, B. O. (2002) Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature 420, 186-9. PubMed
Wagner A (2008) "Neutralism and selectionism: a network-based reconciliation.", Nat Rev Genet 9:965-74. PubMed