So, what is Bioinformatics?
Depending on where you look online, you will find a few different variants to the definition of Bioinformatics. A quick Google search brings you to Wikipedia where you will find that Bioinformatics is “The intersection of biology, statistics, and computer science”. Dictionary.com on the other hand says that Bioinformatics is “The retrieval and analysis of biochemical and biological data using mathematics and computer science, as in the study of genomes”. Jennifer Shalamanov from Udacity goes a step further and distinguishes Bioinformatics from Computational Biology by saying “Both require extensive knowledge of computer science, data analysis, and biology, but bioinformatics is about building the tools for studying biology while computational biology is about studying biology using those tools.” No matter what definition you subscribe to word for word, it is clear to see that there are three main pillars to Bioinformatics:
- Data Science
- Computer Science
The definition that will be used for now to describe the field is:
“Bioinformatics refers to the study and interpretation of large sets of biological data through the use of computational pipelines and models.”
Okay… So what is Bioinformatics used for?
By now you have heard about “big-data” and the massive influx and generation of information that is happening. From smartphones, smart watches, and IoT devices, Forbes wrote back in 2018 that we are generating 2.5 quintillion bytes of data a day, and it has only increased since then. The portion of data that is of interest to us, is the biological data. Bioinformatics is used to help to clean, validate, and interpret the biological data sets that are being generated. Because Bioinformatics is such a broad field, we can say that it is used in applications from pharmacology to antibiotics, from green tech to climate change studies. Anywhere that there are huge biological data sets, you will find the use of Bioinformatics. There are so many applications for the field, that it is better to focus in one a particular area such as medicine or crop science. Even then you can continue to get more specific. Personalized medicine also encompasses drug discovery, personalized medicine, preventative medicine, or gene therapies. No matter what field you go into, if you are utilizing processes to interpret and analyze biological problems, you are in the field of Bioinformatics.
How do I learn Bioinformatics?
By practicing! All jokes aside, there are a lot of resources available online for open learning of the skills necessary to practice Bioinformatics. Rosalind.info is a fantastic website with practice problems as well as explanations of new topics and ideas to help you actually understand what it is you’re doing. There are of course more “traditional” paths you can take, such as attending a university with a dedicated “Bioinformatics” degree, but there are plenty of other avenues for free learning online. Just keep in mind the skills that you should be focusing on when learning Bioinformatics. You will need statistical knowledge, biological domain knowledge, and the ability to program computers to do what you want them to do. But don’t be discouraged; while there is a baseline of knowledge that you might need to get started, part of the beauty is that you will be able to learn as you go. Bioinformatics has the potential to open doors to help unlock the mysteries of Biology, and will only continue to grow and get bigger.