Forum:Importance of Data Structures for Bioinformatics?

Question

[S]

Hello,

I am currently an undergraduate student looking at going to Medical School. I am planning to take one or two gap years, where I want to apply for either an internship or research in bioinformatics / multi-omic analysis.

Right now, I am faced with a decision on whether or not to drop the Data Structures course for my Senior Fall (I graduate this semester). The class goes through data structures, algorithm science, and more general concepts in Java Programming. It is my senior year, last semester, and I do not want to risk hurting my GPA (it is a notoriously difficult class to get a good grade in).

My question is this: how important are Data Structures to multi-omic / bioinformatic analysis, should I take this course, and are there other factors am I not considering? I have heard that polymorphism / object-oriented programming / unit testing are more for backend software development jobs, and that disease research often relies on Pipeline / R / Python / other tools.

Could I still get a role in a Biotech start up or research if I do not take this class? I have taken other coding classes and have undergraduate research that gained me a lot of skills outside of the classroom.

I appreciate any advice you may have. Thank you.

[dsull]

If you don't want to hurt your GPA, why not just take the course pass/fail or, if that's not an option, simply audit it?

I doubt anyone will say "hey, you didn't take this particular course at your particular school so we're not going to hire you".

Answer 1

[d-cameron]

how important are Data Structures to multi-omic / bioinformatic analysis

Generally speaking, they're not critical if you are using an analysis pipeline that uses existing tools and methods to analyse your data/experiments (e.g. running Limma-Voom to find differentially expressed gene). On the other hand, if you are developing new bioinformatics tools/analysis techniques then a strong knowledge of data structures is extremely advantageous. The first group is larger (there are more people using the tools than writing the tools), and the latter group is enriched for individuals with computer science and/or statistics backgrounds.

Answer 2

[xiaoguang]

Bioinformatics is a cross-disciplinary research subject and learning anything is a plus for future participation in related jobs. But right now, there's no need to learn particularly much; learning on the job is the best way to go.