Russ Altman has an interesting post on his blog:Bioinformatics & Computational Biology = same? No.
I spent the first 15 years of my professional life unwilling to recognize a difference between bioinformatics and computational biology. It was not because I didn’t think that there was or could be a difference, but because I thought the difference was not significant. I have changed my position on this. I now believe that they are quite different and worth distinguishing. For me,
- Computational biology = the study of biology using computational techniques. The goal is to learn new biology, knowledge about living sytems. It is about science.
- Bioinformatics = the creation of tools (algorithms, databases) that solve problems. The goal is to build useful tools that work on biological data. It is about engineering.
Personally, I have made the same distinguishing, but for some reason with the terms somewhat reversed. For me, computational biology has always been about the development of methods and tools, while bioinformatics has been about appyling methods to study biology.
I suppose someone can argue with the my use of the term “bioinformatics” as an engineering discipline. That’s fine–I’m open to a different term. But I would ask why bioinformatics isn’t good. I think computational biology is more solid–the ‘biology’ is clearly the noun and the ‘computational’ is clearly the adjective.
Good point for that use of the terms. My reasoning for the other use was that computational biology clearly had a focus on the "computational" and isn't just studying biology by running computer programs.
Anyway, the actual terms are not so important, but I completely agree that the mix of mathematics/statistics, computer science and biology -- whatever we call that mix -- consists of several disciplines:
- Tools and methods development
- Applying tools and methods in data analysis
I wouldn't put the first item, tools and methods development, entirely in an "engineering" box, though. Some tools development is just an engineering exercise, implementing existing well known methods, but some method development involves formalising new hypothesis and implementing ways of checking them into computer tools.
The same goes for the second point; applying tools can range from running data through a pipeline with very little other user involvement to detailed and careful analysis of all computational results compared to the underlying biological hypothesis.