I'm sure the query had underlying motivations with it. Perhaps there's some strong interest in biology but the hesitation to go down a path that leads to counting fish or synthesizing proteins all day. Careers in computer systems are so much more lucrative as well, with a higher pay scale to boot. Have hope! Computer tinkering and fish counting do intersect in the realm of bioinformatics.
What is Bioinformatics?
From what I can tell bioinformatics is taking the huge amounts of data produced from any sort of experiment and making sense of it all. In a broad sense it sounds pretty simple.
1. have data
2. look at data
However, when the amount of data enters into the thousands and millions of entries it become nigh impossible to make sense of them all. Just throw it into a computer, right? That'll sort it all out! But who built the software that can handle the 3 billion base pairs in your DNA?
|Author's understanding of IT stuff.|
Every study and thesis in any form of science has data in need of analysis. From marketing to cancer research the demand is immediate and essential.
Is this coming into focus? For me I can still barely understand it. My lovely computational biologist boyfriend wrote a piece on how he came into the field HERE. It's filled with vocabulary that is often used by super villains explaining their dastardly plans. As a common citizen I can only hope the C. albicans yeast uprising will somehow spare my life.
To become a bioinformatics professional, graduate studies are absolutely necessary. On a lighter note they are also absolutely free. Free graduate schooling for science majors! It's true! The best kept secret of the higher education world is that in return for free graduate schooling through PhD and about $25k a year salary science students must work in a lab as a research assistant and teach at least one semester basic science class. It may vary from school to school on requirements and compensation, my information is from the University of Minnesota. Free school for simply doing school!
|Just your average grad student|
Once students are considered qualified for their chosen science graduate program they find a professor or researcher with enough budget and willingness to take them on. The ease of finding a position is dependent on the program, quality standards of parties involved, space available, and really anything else you could think of as going wrong.
Most labs appear to outsource their data analysis to the local super computing department so they may not think they need an in-house solution or have the capabilities to properly train a student in bioinformatics. Labs that cannot help but have an excessive amount of data such as one that works in genetic testing will be more open to spending money on students looking to split their time between computers and research.
The frustration of speaking to those with dream jobs come from the complete lack of direction they claim to have had during their journey. I just kinda fell into it! they say. Sure. Sure you did. Uh-huh. Years of training and knowledge just happened to you on accident.
Pointed questions and uncomfortable silences later I bring 3 different paths into bioinformatics to help shed some light on this non-traditional field of study.
|That soul was totally worth the PhD|
The common thread throughout his life has been a deep love of biology. Combined with his seemingly natural talent for programming (his brother claims he started in 1991 simulating fish on a DOS system) he is particularly well suited for computational biology. However, I would like to point out that when he went through undergrad (late 90's) computational biology was not taught in any way shape or form. Had he continued a traditional student path straight on to graduate school he may not have been able to become a computational biologist. This is the path of most resistance, one where the job is just beginning to take shape so there is a distinct lack of direction.
Example number two is the first computational biologist to go through Darren's lab, his predecessor. Whereas Darren approached the subject from a biological point of view this gentleman spent his undergrad studying programming and had biology as a side project. Coming from that direction has an interesting effect on the work produced. It's more sophisticated but less worker friendly in that the programs written are able to handle more complicated and larger data sets but the output remains in geek-speak. Both approaches have their merits. Coming from a computer background also allows the student to have a high paying fall back career (Don't give me that look like money don't matter) and provides a gateway into any science or data analysis career.
Finally my last friend is completing his bachelors degree in computer science soon and has a sweet job at a super computing department. Super computing departments, as mentioned before, process most of the data analysis for genetics labs. They pack it up into nice little files for normal computers and scientists to handle. They do not interpret the data, simply process it. He's currently working on a mycology genetics project (which is so amazing cool, mycology is fascinating!) but has no particular knowledge or interest in mycology as far as I can tell. His job is an essential part of the research. It could not be completed without him. Is he deserving of a lab coat and scientist label? I give this example because if the urge struck he could go in that direction. It's a place to start from.
So where to start? Still in undergrad looking at all the options available?
Beyond checking if your school offers a bioinformatics course or has a computational biologist on staff you can talk to there are a couple different options. Coursera, the completely free education website, has offered a couple different bioinformatics classes that you need in your life! I attempted one and have decided to come back to it when my biology vocabulary is larger.
It is also reported that a solid background in Linux is needed. Python understanding is recommended. That sounds a bit dirty to me.
Rosalind is an amazing resource for getting started in the field. It starts from the bottom up, I can't say enough good things about it.
I hope this guide has been helpful in some way! It was a pleasure looking into all of it. Good luck on your journey!