Bioinformatics Zen

In World of Bioinformatics Quest^TM (WoBQ) having the right character that suits your style is essential. You may think that a hot shot Rubyist is the coolest class to be, but remember that you have to play this character for the next 50 years. In general it’s better to be a character that you’ll enjoy playing, rather than one that will get you more publications but have less fun with. This page will guide you through all the parts of character generation for WoBQ.

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I think the title says it all. If you have two populations such as “Treatment” and “Control”, what type of graphs can you use to compare the two? Have a look at the examples, then pick the corresponding R code.

All of the charts come from either excellent the lattice package, or the superb ggplot2 package. The code should also work for multiple populations as well.

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Back from a weeks holiday in Hungary just in time for my, hopefully, last ever year as a student. Last month I had a flurry of work completing a report and poster for the end of my second year, but now I’m aiming to work hard and try and get at least two papers out in my final year: in time to write up my thesis.

But now, to coincide with the beginning of the academic year, and the time that new PhD and Masters students start, I thought I would share some the resources that I found useful through out the course of my own Masters degree, then first two years of PhD.

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In other words, you’re a bioinformatician, and data has been dumped in your lap. Find the patterns, trend, answers, or what ever meaningful knowledge the data is hiding.

From experience, I can say that is one of the most frustrating positions to be in. Data mining is a huge field and can easily be bewildering for a beginner. However, high through-put techniques in molecular biology require, more and more, that bioinformatics is required to interpret the data. Furthermore, people working in bioinformatics generally come from computer science, or biology backgrounds. Data mining, however, involves statistics to one degree or another, which means entering a field that is may not be your strong point.

Here are some tips from my own forays in the quagmire of data mining in bioinformatics. Hopefully this will give you some guidance, and an introduction to starting.

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