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Happy to see that The Self-Weighting Model (SWM) paper

(http://www.tandfonline.com/doi/abs/10.1080/03610926.2011.654037)

was briefly cited in the Virus Evolution journal published by Oxford University Press, in the research paper:

Coevolutionary Analysis Identifies Protein–Protein Interaction Sites between HIV-1 Reverse Transcriptase and Integrase

HTML version: http://ve.oxfordjournals.org/content/2/1/vew002.full).

PDF version: http://ve.oxfordjournals.org/content/vevolu/2/1/vew002.full.pdf

This is a great example of applying data mining techniques to HIV research, a major public health issue according to WHO, UNAIDS, and other world health organizations.

The study agrees with the SWM thesis; i.e., that correlation coefficients are not additive. Glad to see how SWM influenced their data analysis.

More on SWM below:

http://www.minerazzi.com/tutorials/self-weighting-model-tutorial-part-1.pdf

http://www.minerazzi.com/tutorials/self-weighting-model-tutorial-part-2.pdf

Time to restore online my old tutorials on the non-additivity of correlation coefficients so the next generations of scientists are not misled (@SEO quacks and @MOZ pseudo-scientists).

 

 

 

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