Lecture Slides


Papers Mentioned During Class

  • Rob Phillips and Ron Milo (2009), A feeling for the numbers in biology, PNAS 106, pp. 21465-71.

  • Schmidt et al., (2016), The quantiative and condition-dependent Escherichia coli proteome, Nature Biotechnology 34(1), pp.104-110. (supplemental information)

  • Rob Phillips (2015), Theory in Biology: Figure 1 or Figure 7?, Trends in Cell Biology, 25, pp. 723 - 729
    Rob's constant argument that we should also try to formulate theories that guide our experiments rather than establishing a model after the experiment was done.

  • Cohen, J. E., (2004), Mathematics Is Biology“s Next Microscope, Only Better; Biology Is Mathematics” Next Physics, Only Better, PLoS Biology, 2(12), e439.

  • Garcia, H. G., & Phillips, R. (2011), Quantitative dissection of the simple repression input-output function, PNAS, 108(29), p12173-12178 and Brewster and Weinert et. al., (2014), The Transcription Factor Titration Effect Dictates Level of Gene Expression, Cell, 156(6), p1312-1323
    Two cool papers that demonstrate we can quantitatively predict protein expression from the simple repression regulatory construct. Each uses a different way to count the lac repressor copy number in E. coli

  • Williamson, J., (2008), Cooperativity in macromolecular assembly, Nature chem. bio., 4(8), 458-65.
    Paper mentioned by Jane in lecture where he argued that sometimes using the mass action principle rather than the statistical mechanics framework can turn the math into a very messy business.

  • Gunawardena, J., (2013), Biology is more theoretical than physics, MBoC, 24(12), 1827-9.
    Jeremy mentioned that many ideas in biology were first conceived purely as theoretical entities until experimental evidence proved their existence.

  • Gunawardena, J., (2014), Models in biology: 'accurate descriptions of our pathetic thinking'., BMC biology, 12, 29.
    Jeremy's argument on how mathematical models allows us to accurately state our pathetic beliefs on how a system works.

  • Gunawardena, J., (2013), A linear framework for time-scale separation in nonlinear biochemical systems, PLoS One, 7, 5.
    Paper related to Jeremy's talk on how to use graph theory to reduce the molecular complexity of biochemical networks.

  • Gerhart J., Kirshner, M., (2007), The theory of facilitated variation, PNAS, 104.
    Paper mentioned during Jeremy's lecture on the concept of weak linkage

  • Mohapatra L. et al., (2015), Design Principles of Length Control of Cytoskeletal Structures, Annual Review of Biophysics, 85-116.
    Excellent review from Jane's group on different models for cytoskeletal length control.

  • Anderson P. W., (1972), More is different, Science, 177(4047), 393-96.
    Paper mentioned during Jane's lecture on the relevance of coarse-grain modeling of complex systems.

  • Henley, Christopher L., (2012), Possible origins of macroscopic left-right asymmetry in organisms, ArXiv.
    This paper was mentioned by Jane in class. It was written by his PhD advisor Chris Henley and though “speculative”, offers the kind of overarching explanation of many different examples of symmetry breaking that occur in biological systems. See pg. 36 for Henley’s argument for treating all of these examples as one idea rather than on a case by case basis


    Course survey


  • [ Link to the post-course survey ].