I want major in bioinformatics, can you tell me something about this major?
What is the job outlook for bioinformatics professionals in the coming decades?I'm planning on earning a bioinformatics degree during my undergraduate degree, and I was hoping to learn the prospects of the career, itself, should I choose to pursue further education in the field. I was hoping to hear about how demand is predicted to rise/fall in the coming decades and whether it is a job that is easy to outsource. #college-major #job #bioinformatics
4 answers
Isabella’s Answer
Moving forward, I would recommend immersing yourself in the world of bioinformatics by reading articles, reaching out to bioinformatics people, learn some R code, and making connections to help get some more exposure (and to just meet some amazing individuals who can give even more career advice). Good luck!!!
Bryan’s Answer
Although it is not my area of expertise, I have worked with several computer consultants who had microbiology and cancer research in their backgrounds. These computer-focused people worked at places like the Institute for Systems Biology and the Fred Hutchinson Cancer Research Center in Seattle. One coworker who had specific bioinformatics experience used software to analyze gene sequences, and I think the idea was to search for patterns in the sequenced genes. A quick search online tells me that's essentially what bioinformatics is--finding patterns in gene sequences. [A better search tells me there's much more to it than just finding patterns in genes. Although that is one aspect of it, there's a lot more to it and it includes more than just biology and computers. ]
Because this field is at the intersection of biology and technology, it seems there are two ways to approach that major--through computer science or through biology. I'm sure there many more than just these two ways to get into bioinformatics, but these seem like reasonable places to start if you're looking at a major.
The people I know who worked in microbiology spent their time researching and publishing their research. They created protocols (plans) to run experiments in laboratories. These experiments required that they do a great deal of research before they chose the direction of their experiments, and often they were advised by more senior scientists or groups of scientists they worked under who guided them in their work. The work they did was very meticulous and required great care to ensure that they did not contaminate the substances they were working with during the experiments (in incubators for example), and this painstaking attention to detail and very careful work extended to the analysis of the results of the experiments using tools like a mass spectrometer. There seemed to be a larger proportion of people from other countries working in the microbiology field, which was nice.
The technology approach to bioinformatics might be more focused on automation of experiments or integration of lab equipment to help gather data on the experiments, or it could just as easily be software development focused when analyzing data that was gathered on experiments. This last item of analysis was what a coworker had done when searching for strings in sequenced genes. From what I remember, the experiments were planned with help of more senior scientists. Then, the steps of the experiments were automated somewhat to make it easier to follow the strict sequence and duration of the steps in the experiment. To do that they used equipment that stirred samples continuously at variable rates over the course of many hours or days, other equipment that combined substances at a specific time, or equipment that heated the substances or maintained certain conditions required by the experiment for very precise amounts of time. All of this experimental automation would generate data that had to be recorded in a form that could be easily analyzed later on. So there seem to be three technology-related paths into bioinformatics that I can see--computer-controlled automation to run the experiment, data capture or logging to record the experiment, and software that helps with analysis of a huge amount of data. That gene data is really big, and it can take a lot of computing power to look through all of that for genes with the particular properties you might be interested in finding with your experiment.
So you could probably look at courses in biology or microbiology and get a few courses in software development. If you look at software development, make sure you get some understanding of regular expressions that you can use for pattern matching, and try to learn a scripting language that is somewhat popular. That'll help you search through large amounts of data for the genes you want, but it'll also give you a bit of experience programming, and knowing a common language (like python or perl) will be useful no matter what field you go into. Since the data you generate in this field is big, you might want to look into some database technologies that are popular for Big Data. The reason I mention popularity in both the scripting language and database technology is that if you change your major or become more focused on technology, then you will be able to re-use the skills you learned in bioinformatics toward another major like computer science. Best wishes! :)
Bryan recommends the following next steps:
Toshiro K. Ohsumi
Toshiro K.’s Answer
The demand for *good* bioinformaticians is very high right now and likely will stay that way for a while. Having said that, a lot of bioinformatics jobs are outsourced to companies in other countries with less demanding salaries. I think the traits of a bioinformatician that is hard to outsource are:
1. They can develop, say, a novel algorithm for analyzing new biology.
2. They are very fast at implementation of an idea. In part, they should be relatively fast coders.
3. They have a diverse skill set. For example, they know not only coding, but also databases, statistics, and molecular biology.
4. They are mathematically rigorous. If one develops new analyses, it is essential for the analysis to be statistically justified.
5. They can communicate well, particularly with biologists. Bioinformatics is inherently a collaborative field and thus a team-first mentality is important.
Someone who embodies the above are quite rare. (I'm trying to find someone like the above to hire.) I think it is important not to be a jack-of-all-trades-master-of-none (an issue I've seen in some computational biology candidates), but one should master at least two of the above. However, if a candidate truly embodies the above, then a lot of companies will be competing for their services. I hope this helps. Best wishes.