Previously, I wrote about organising your file system to make the relationships between files that produce data, and files containing data more descriptive. One of the best tips I’ve been given, is to store all my data in a database. Regardless of what the data is, or how “mission critical”. Here are some reasons to use a database, rather than files, to store your data.
I spent several hours today implementing a sequence analysis method taken from a paper I had read earlier. I created a database, downloaded yeast coding sequences, then coded the whole method up in java. Shortly after doing this, a google search showed that not only had a tool been published to perform this analysis, but that the original method I implemented was flawed.
I think the lesson here is to always check what the goal is of the research. Before touching the keyboard. Do you sometimes find that it’s easy to get bogged down in the individual details of implementation, such as coding, rather than the higher scientific question. Coding is enjoyable and is one of the reasons why I like bioinformatics. But what I have to keep telling myself is that in the end it’s about the science rather than the details of implementation. If someone else has already created a tool, or even better produced the results I’m after, then I can skip this step and start the intended analysis. Plus my implementation is probably a lot worse than someone who has given the problem a lot more consideration.