Resources

On this page, we have collected links to resources we have found useful.

Online Resources

Print Resources

  • A Primer on Scientific Programming with Python (4th edition) by H.P. Langtangen. Springer. (2014)

  • Physical Models of Living Systems by Philip Nelson. W. H. Freeman and Company. (2015)

  • Learn Python the Hard Way: A Very Simple Introduction to the Terrifyingly Beautiful World of Computers and Code (3rd edition) by Zed Shaw. Addison-Wesley (2014)

  • Computational Physics: Problem Solving with Computers (3rd edition) by R.H. Landau, M.J. Parez, and C.C. Bordeianu. Wiley-VCH Verlag GmbH & Company (2012)

  • A Student’s Guide to Data and Error Analysis by H.J.C. Berendsen. Cambridge University Press. (2011)

  • Python Scientific Lecture Notes by V. Haenel, E. Gouillart, and G. Varoquaux. (2013)

  • Python for Biologists: A Complete Programming Course for Beginners by M. James. Amazon CreateSpace. (2013)

  • Computing for Biologists: Python Programming and Principles by R. Libeskind-Hadas and E. Bush. Cambridge University Press. (2014)

  • Python Pocket Reference (5th edition) by M. Lutz. O’Reilly Media Inc. (2014)

  • Computational Physics (revised and expanded edition) by M. Newman. Amazon CreateSpace. (2013)

  • IPython: A system for interactive scientific computing. F. Perez and B.E. Granger. Computing in Science and Engineering 9(3), 21–29. (2007)

  • Ten simple rules for better figures. W.P. Rougier, M. Droettboom, and P.E. Bourne. PLOS Computational Biology 10(9), e1003833. (2014)

  • Avoiding twisted pixels: Ethical guidelines for the appropriate use and manipulation of scientific digital images. D.W. Cromey. Science and Engineering Ethics 16(4), 639–667. (2010)

  • Optimal matrix rigidity for stress-fibre polarization in stem cells. A. Zemel, et al. Nature Physics 6(6), 468–473. (2010)

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-- Jesse & Phil