Bioinformatics Misconceptions

I just read an interesting paper on the three common misconceptions people normally have about the field of bioinformatics. I’ve been eyeing bioinformatics as a possible venue for bringing more people into DIY sciences, so I took some notes for future reference. It turns out that I’ve been suffering from same hype and illusion about the field of bioinformatics just like the vast majority of the non-specialists out there.

Simply put major misunderstandings about bioinformatics might be narrowed down to three myths permeating the science culture, according to the author.

Myth#1: anybody can do this
-bioinformatics is inexpensive
-bioinformatics software is free

Myth#2: you’ll always need an experiment
-bioinformatics is a rapid-publication field
-all bioinformatics does is generate testable predictions

Myth#3: this is news technology but technology nevertheless
-bioinformatics is a new field
-bioinformatics is an application discipline

*FYI the statements under the Myth headings are the ones the author refutes in his writing.

Myth#1 is that everybody can do bioinformatics, using only the cheap or opensource tools available off the net. The author does admit that this is indeed the case to certain extent. However once you get into any serious large scale research about or involving bioinformatics the initial assumptions will prove to be a burden on the organizational level. As the author will elaborate in later parts, bioinformatics is a field of scientific research on its own not subservient to the conventional wetlab biology. Indeed, while reading the article I was under the impression that the main statement for the whole article revolved around how people do not realize that bioinformatics is a field of scientific research with its own goals and complications. Very unlike the laymen assumption that bioinformatics is in fact just biology done with computers, or application of computerized tools to wetlab based biological research just like how the researchers would use word processors or LaTeX to type up their reports. Personally I found it a little disheartening that bioinformatics research is just as complicated as any other field of scientific research for DIY implementation, possibly more depending on what the amateur scientist is trying to do. But then I can only blame my naivety. The author also makes a point that bioinformatics can be very expensive to begin due to some number of proprietary software services that must be purchased (never went into much detail on that. I guess it’s different according to the theme of the research?) and the resources needed to write and maintain codes for the project. It makes sense when you think about it. While it would be possible to come up with some bioinformatics application in-house, after certain level it would be vastly cheaper to simply buy some number of components and just use in-house resources to link them and tune them into giving results needed for the project (which shouldn’t be easy to begin with).

Of course, I still think that we can, and maybe should, use some approaches of bioinformatics to provide interesting DIY science framework to the public, like the Annotathon metagenome annotation project that had been open to the public for a while now. I’m just glad that I got a chance to listen to some of the intricacies of the field from someone already working with the tools of the trade.

While I now understand some stuff about what the field of bioinformatics is about, I’m still unsure as to what kind of project idea I can come up for DIYBio curriculum using the technology… It’s a problem I’ve been running into a lot lately in doing stuff involving DIYBio. I know there are tools and tutorials out there, but I just can’t seem to be able to put them together into a coherent whole. DIYBio needs some sort of project that would turn knowledge into skill… More on that later.


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