Explanatory First Post: What R U Doin?

OH HAI.

I am starting this blog because of the atrocious lack of easy-to-read explanations for some technical topics (i.e. ones that interest me) in computer science. For sure, there is a wealth of excellent knowledge about many popular topics in the interwebs, for example the plentiful Java/OO/C/Complexity resources.

However, some topics that are of less interest to hobbyist programmers have web resources limited to jargon-tastic journal articles and despairing, unanswered forum questions. 

Sometimes there are also lecture slides that look like this.

One such topic is BIOINFORMATICS, so I’m going to BLOG about it!

BIOINFORMATICS: WHO GIVES A SHIT?

Firstly, what is bioinformatics? In the context I’ll be discussing, it’s the design and use of software for biological research.

Coding while wearing a lab coat and safety glasses technically also counts as bioinformatics.

How does software help biological research, you ask? Won’t the computer get slime on it? Don’t be ridiculous. Software in this field is intended for analyzing data collected for biological research. And it’s incredibly important, because the amount of data required in biological studies is enormous. That’s because they involve:

•        Huge numbers of variables per test subject. The human genome has about 20,000 genes – handling them could slow a program to a crawl for just a couple of test subjects if you aren’t careful with your Big O. In contrast, I know a sociology student doing postgraduate research with only two variables of interest (socioeconomic status vs. number of piercings).
•        Huge numbers of tests required. There are so many different environmental and genetic factors influencing a person’s health that finding trends in biological data means you have to sift through a discouraging amount of noise. The main way to combat that? Testing EVERYONE. Or failing that, testing as many people as you can.

Go ahead. Find trends in that just by looking at it.

It’s wildly impractical for researchers to deal with this data without software to automate the process. Therefore, bioinformatics is important, the people who do it are super studs, and my impending blog posts are justified.

Bonus Links:

• An even more professiorial introduction to bioinformatics.

Next post: Actual content! Get ready!