CogsOver the last few months I’ve been spending more and more time with R. Not only R but also Bioconductor packages which allow me to easily work with the massive data contained within the microarrays I’m currently looking at.

As this is my first post about R, statistics and Bioconductor, I won’t go over the various things I believe should change within the R/Bioconductor community. I’d rather just take this opportunity to show my appreciation for such a cool and powerful tool, or should I say, set of tools.

From simple statistics to amazingly complex visualizations, I’ve slowly grown to fall in love with R. Well, I love and hate R. But I’ll keep things positive for now.

Where my biggest interest falls is in the interface between data and art. Visualizing data in interesting and new ways that allow us to extract new or better understanding from said information. This is what I hope I’m moving towards as I spend many and long hours coding R and attempting to find patterns in my scores of biological data.

Another side effect from spending so much time sifting through data sets is seeing data everywhere. It’s as if everything can be re-analyzed or further processed to produce new and interesting results.

Simple things like waiting at the bus stop lead me to think that it would be interesting to see how efficient the buses are or if their routes could be improved. Looking at the seating in the cafeteria makes me consider the many possible optimizations in table/chair positioning, etc.

I know that this is not necessarily due to R or data but rather more interest in mathematics and statistics. However, the fact that I live and breathe R, statistics and data sets has been making the cogs move…

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