Principal component analysis

Easy to read, simple paper highlighting the different aspects of PCA and related diagnostic tools. Good reference for the future.


H. Abdi and L. J. Williams, Principal Component Analysis, Wiley Interdisciplinary Reviews:  Computational Statistics, 2, 2010.

A Tutorial on a Practical Bayesian Alternative to Null-Hypothesis Signifiance Testing

A little, easy-going paper on Bayesian vs. Pearson/Neyman framework. Easy to read and easy to follow.

M. E. J. Mason. A Tutorial on a Practical Bayesian Alternative to Null-Hypothesis Signifiance Testing. Behavior Research Methods, 2010.

Biochemistry correlates with geochemistry

I always wanted to somehow test the hypotheses how the changes in geochemistry (most importantly, increase in gaseous oxygen) affected the evolution. Here is a paper where exactly this is shown: that the emergence of certain protein domains correlates with global geochemistry changes.

Protein domain structure uncovers the origin of aerobic metabolism and the rise of planetary oxygen. Kim et al. and Caetano-Anollés. Structure 2012

Evolution of the adaptive immune system

A neat review discussing the evolution of the adaptive immune system. Plenty of interesting stories on fish!

Origin and evolution of the adaptive immune system: genetic events and selective pressures. Flajnik & Kasahara, Nature Rev. Genetics 2010

Another interesting paper that puts the genome sequence of the Atlantic cod in the context of immune system evolution

The genome sequence of Atlantic cod reveals a unique immune system. Star et al. and Jakobsen, Nature 2011

Know when your numbers are significant

It is always nice to see a paper in a major journal that deals with statistics. Here, a popular commentary on statistical testing and significance in Nature. It includes a few simple rules that any biologist — with statistical training or without — should be aware of.


David L. Vaux, “Know when your numbers are significant”, Nature 2012

PLS-DA citation

Paper to cite when using PLS-DA based on microarrays in a clinical context: “Prediction of clinical outcome with microarray data: a partial least squares discriminant analysis (PLS-DA) approach”.


Pérez-Enciso & Tenenhaus 2003, Hum. Genet.