What is computational research?
Computational research is another method of conducting independent research projects that require a computing device, knowledge of data analysis software, some computer language skills, and of course, a strong scientific question. This mode of research is convenient as it does not require intense safety training or even commuting to an institutional laboratory (for the most part). Instead, HS students can take advantage of free and publicly available data sets to extract vast amounts of information.
Pros and cons of computation research
Pros
- Researchers can conduct analysis of large data sets more efficiently than methods such as wet bench experimentation. This leads to fewer false leads pursued and an expedited discovery process.
- Published code can be used (and of course cited) to more easily reproduce results of other researchers and be incorporated into your own project.
- Running protocols or experiments is more flexible since it can be done with a computing device in your own home rather than requiring expensive and complicated machinery.
Cons
- Computational research can often demand intense computing power that cannot be provided by every computer. For example, minimum specs might need to be met in order to run a program.
- There is a lack of standardization of methodologies and workflow across the field.
- While it is convenient to be able to use source packages produced by other computational researchers, they do not always work well and sometimes require time to debug them.
- Small changes in code can dramatically influence the results, meaning that computation research is not especially resistant to user errors.
What does computational research look like? See some of our members in action!
How to know if computational research is right for you:
Self-Driven
Like all research projects, you must ultimately be the driving force; however, for computational research this is magnified as much of the work will not be done under any supervision whatsoever (versus having a mentor in the lab making sure you are safe).
Good with computers/coding
A pre-requisite for computational research is that you at least have some background in computer science. If not, you should start by learning from classes before trying to tackle a research project.
Available resources
Sometimes there might not be a university near where you live, so the only research that can really be done is either computational research or field work. You will need computer tool/software with the RAM, storage, etc. required to properly analyze your datasets and run your code. You will also need to pick (and stick with) a programming language, software programs (ex. Excel, GSEA, Cytoscape), packages (ex. Pandas, NumPy, ggplot2, DESeq2), and other visualization tools (ex. Prism GraphPad). It is essential that you have access to a dataset of interest that you will base your research off of. Lastly, you will need to have some statistical knowledge to understand significance, tests, how to draw conclusions, etc. (although this is true for not only computation research).