5 tips for getting into computational biology

By Fatima Vayani, King’s College London

I discovered computational biology (or bioinformatics, as it is also known) by chance during an internship when I was 17. I have always been a curious person, and from a young age was inclined to the life sciences. Having been surrounded by computers since childhood, however, I was excited by the notion of exploring nature without having to be in nature itself. Those who prefer not to work in the field or in a wet lab still have the ability to do biological research through computation!

If I hadn’t come across the field during my internship, my first encounter would have happened in the third year of my undergraduate degree, when I was given the choice to take a bioinformatics module. As personal genomics companies like 23andMe have now become household names, bioinformatics is less of a black box, but it’s always a good idea to get ahead of the game!

  1. Do your homework. Bioinformatics is a very wide area of research. The area is defined by the use of computational methods for biological research, but these methods vary greatly, depending on the type of data and applications. Not only does it include analysis of genomic data, it also covers computational drug development, computational phylogenetics, gene expression analysis, image analysis and more. Each specific area uses a set of methods that lend themselves more to computer science, mathematics, statistics or engineering; so you can find a speciality that suits your skills and passion.

    The specific area I work in is computer science. In fact, I spend most of my time on theoretical computer science: designing (as in the photo) algorithms to answer biological questions. Once an algorithm is designed, it is implemented as a software tool for use by biologists or bioinformaticians (Taken from my Instagram page).
  2. Become comfortable with using computers for research. Depending on your research project, you may or may not need to know how to code. Don’t be intimidated by the idea of it, give it a good go, but if you don’t enjoy it, know that you can find many projects that don’t require coding skills. If you are a complete beginner, I would recommend learning to code from YouTube tutorials. If you are into statistics, learn R or Matlab, and if not, learn Python first and then move on to C++ or Java. If you run in to errors when compiling your code, search your error message on Stack Overflow. To familiarise yourself with some bioinformatics tools and databases, head to NCBI’s resource list. If you run in to problems using these tools, seek help on BioStars.

    Here, I was testing the implementation of an algorithm. We always test two things: accuracy (is the output correct?) and efficiency (how fast is the output produced?) (Taken from my Instagram page).
  3. Talk to people. Search the internet for academics, organisations or even meetup groups that are in the field. E-mail them with questions, ask for opportunities to shadow or work with them, attend their seminars and networking events. One of the best (and most fun!) ways of learning the current climate in a field is by talking to people. Don’t be afraid of reaching out to senior scientists; people love helping others. I would recommend starting off with ISCB and in particular, their student groups, which are in almost every country!

    Me giving a talk at the University of Cape Town Medical School, South Africa (Taken from my Instagram page).
  4. Read magazines, blogs and Tweets. Exploring such a vast yet niche field can be confusing, so don’t go right in to reading academic papers! Magazines such as Front Line Genomics are great to keep up with the current state of the genomics industry, and Twitter is even better if you follow experts in the field. Follow my Twitter list for a curated feed of research news, and check out the resources page on my website for a list of bioinformatics blogs.
  5. Be passionate and curious. Though I have suggested ways to learn a lot about bioinformatics before you are taught it formally at university, I myself was never given this advice. The one and only thing that will truly drive you to any specialism is passion. If you are curious about any field, and learning about it excites you, you have enough to enter the field – don’t worry about whether you have the skills yet.
The sequence pictured is the latest major release of the human reference genome GRCh38 from the 1000 Genomes Project (Taken from my Instagram page).

HeadshotAbout me 

I am a final year doctoral candidate at King’s College London. I have an undergraduate degree in biology, a postgraduate degree in bioinformatics and am currently working on the development of algorithms for biological sequence analysis. Outside of my research, I am an active member of the science community: organising bioinformatics conferences and seminars; working on diversity initiatives and engaging the public through my blog and social media. You can find out more about me at www.phdomics.com and also interact with me on Twitter and Instagram.

Interested in learning R? Register for R for Biochemists 101 online training course starting 14 May 2018, developed by the Biochemical Society.

2 thoughts on “5 tips for getting into computational biology

  1. Very informative post related to clinical research. It is great help for my new project .By reading this article, I learn some important things that I need to improve. I continuously check this site for regular updates in field. Thanks for putting top notch content in article. I would like to be here again to find another masterpiece article.


  2. I am sarvesh currently waiting for my twelth board exams and undergoing coaching for mbbs enterance exam. Ian a little curious to know more about bio informatics / computational biology and in India how to get started. What should I do after 12th my syllabus being physics-chemestry- biology-maths-information technology. Please advice.


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