Bioinformatics Zen

One of the differences between researching a scientific problem using a computer, and developing software, is the approach to writing code. If you’re producing a bioinformatics application there is more emphasis on generating high quality, flexible code, as this makes future maintenance easier. On the other hand if you’re trying to find the answer to a biological question using a series of scripts, then the focus is on the results, rather than the standard of code. During my work, the number of scripts I have tends to grow quickly, and this leads to problems with maintaining dependencies across scripts. Examples of this can be database connection parameters, or the file system location of a library I’m calling. This is because the fastest way to get this information into a script, is to cut and paste from an already existing one. However this becomes difficult to manage, when something changes, because I have to go back through all my scripts and update each in turn.

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A common task in bioinformatics is to read data from a set of files, arrange into the required format, then run an analysis to verify or falsify your expectation. An example would be reading in the yeast interaction network, and protein evolution rates, then correlating the two sets of data to see if there is a trend. Using Perl, you would specify how each file gets read in, arrange the sets of data by gene name, then correlate the two.

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