Reading assignments
- Week 1
- Chapter 1 in Sivia
Eddy, What is Bayesian statistics?
- Week 2
- Chapter 2 in Sivia
Nuzzo,
Statistical errors; see
also the
editorial in Nature
Rougier, et al., Ten simple rules for
better figures; see
also original Python code to generate
figures in the paper.
- Week 3
- Chapter 3 in Sivia
- Week 4
- Chapter 4 in Sivia
- Week 5
- Chapter 23 in MacKay
- Week 6
- Chapter 8 in Sivia
- Week 7
- Dan
White's intro to image processing
- Week 8
- Chapters 9 and 10 in Gonzalez and Woods
- Week 9
- Dan
White's tutorial on colocalization
Bolte, A guided
tour into subcellular colocalization analysis in light
microscopy
Source papers for data sets
- Kleinteich and Gorb, Tongue adhesion in
the horned frog Ceratophrys
sp., Sci. Rep., 4, 5225,
2014
- Gardner, Zanic, et al., Depolymerizing
kinesins Kip3 and MCAK shape cellular
microtubule architecture by differential control
of catastrophe, Cell, 147,
1092-1103, 2011
- Prober, et al., Hypocretin/Orexin
overexpression induces an insomnia-like
phenotype in zebrafish, J. Neurosci., 26,
13400-13410, 2006
- Good, et al., Cytoplasmic volume
modulates spindle size during
embryogenesis, Science, 342,
856-860, 2013
- Reeves, Trisnadi, et al., Dorsal-ventral
gene expression in the Drosophila embryo
reflects the dynamics and precision of the
Dorsal nuclear
gradient, Dev. Cell, 22, 544-557,
2012
- Rasson, et al., Filament assembly by
Spire: key residues and concerted actin binding,
J. Mol. Biol., Epub ahead of print, 2014
- Weitz, et al., Diversity in the
dynamical behaviour of a compartmentalized
programmable biochemical oscillator
Nature Chem., 6, 295-302,
2014
- Goehring, et al., FRAP analysis of
membrane-associated proteins: lateral diffusion
and membrane-cytoplasmic exchange
Biophys. J., 99, 2443-2452,
2010
- Lee, et al., Membrane shape as a reporter for applied forces
PNAS, 105, 19253-19257,
2008
- Iwer-Biswas, et al., Scaling laws
governing stochastic growth and division of
single bacterial cells
PNAS, 111, 15912-15917,
2014
Books
- D. S. Sivia, Data Analysis: A
Bayesian Tutorial, 2nd Ed., Oxford
University Press, 2006.
- Gonzalez and Woods, Digital Image
Processing, 3rd Ed., Prentice-Hall,
2007
- Phil Gregory, Bayesian Logical Data
Analysis for the Physical Sciences,
Cambridge University Press, 2005
- David MacKay, Information Theory,
Inference, and Learning Algorithms,
Cambridge University Press, 2003. (Available
for free online from the link.)