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How to Become a Bioinformatician

A picture of a scientist's hands holding a tablet with scientific notations surrounded by a microscope and scientific equipment to represent someone with a career in bioinformatics

Interested in a career in bioinformatics? We’ve got the lowdown on the training you’ll need to pursue this career path, and a handy list of resources to get you started on your learning.

What is Bioinformatics?

Bioinformatics is an interdisciplinary field that combines mathematics, computer science, physics, and biology to help answer key questions in modern biological sciences research. Bioinformaticians generally work in multidisciplinary groups comprising people from different research backgrounds.

What Does a Bioinformatician Do?

A bioinformatician uses tools to understand or solve biological problems and also helps to develop tools for research. There are two general categories of bioinformaticians.1

  1. The first category includes developers who implement algorithms and develop tools for bioinformatics.
  2. The second category includes curators who are responsible for all the work relating to data resources and data integration.

Most bioinformaticians work within different medical science and health fields, including biology, genetics, proteomics, and pharmaceuticals. Some professionals come from a biomedical research background while others specialize in computational tools.

Skills Required for a Career in Bioinformatics

You’ll need at least a Master’s degree, as well as the ability to program, and you’ll need to be able to learn, and use, complex technology. A number of universities offer bioinformatics degrees.

Here we’ve outlined some of the skills you’re likely to have to master if you decide to pursue a career in bioinformatics.

1. Bioinformatics Skills

You need to learn how to use:2,3

  • sequence alignment tools such as Blast or Bowtie;
  • the Genome Analysis Toolkit (GATK);
  • software for next-generation sequencing, microarray, qPCR, and data analysis (Partek);
  • tools for handling high-throughput sequencing data (e.g. samtools);
  • tools such as Ensemble to gather gene data sets;
  • tools for database search systems (e.g. Entrez).

2. Statistical Skills

You need to learn:

  • how to use statistical software systems such as SPSS and SAS;
  • how to perform statistical analyses with Python or R.

3. Programming Skills

You should be familiar with:

  • one or more of the following programming languages: R, Perl, Python, Java, and Matlab;
  • machine-learning tools and libraries such as Mllib and Scikit-Learn in Python.

4. General Biology Knowledge

This requirement will vary according to your area of study or the particular job you are applying for. You will most likely need knowledge of molecular biology, genetics, and cancer biology.

5. Knowledge of Genomics and Genetics

This knowledge is the core of bioinformatics. Some of the most important skills are high-throughput sequencing, next-generation sequencing, and computational genomics.

6. Database Management

This requirement includes traditional relational databases, which are the basis of SQL (e.g. SQL Server and Oracle). You should also have an awareness of NoSQL databases, which are non-relational, distributed, open-source, and horizontally scalable (e.g. MongoDB).

You also want to make sure you have some knowledge of big data databases (e.g. TCGA) and big data analytics databases (e.g. Vertica).

7. Data Mining and Machine Learning

Knowledge of techniques such as hierarchical clustering and decision trees would be useful in any bioinformatics role.

8. General Skills

In addition to the technical skills mentioned above, you’ll need a range of transferable skills, including the ability to multitask and to work independently, good communication skills, curiosity, analytical reasoning skills, and managerial skills.

Free Learning Resources For a Career in Bioinformatics

Below are some free resources to start learning the skills you will need to pursue a career in bioinformatics.

SPSS

SPSS-Tutorials have a range of tutorials on data analysis and various statistical tests.

SAS

SASCrunch provides a list of free resources to help you learn SAS.

Python

If you’re just starting out with Python, Bioinformatics Programming Using Python: Practical Programming for Biological Data by Mitchell L. Model is a good starting point. After that, you should get familiar with NumPy for vectorized array computation. scipy is also very useful for some special functions or linear algebra.

If you want to process large data, you will need to understand some of the Python-C binding (e.g. SWIG, ctypes, Cython) for high-performance data processing in C and manipulation in Python.

R

David Romney provides a list of online resources for learning R.

Perl

Using the Perl online library, you can access either Beginning Perl or other advanced documents depending on your level of expertise.

Java

There is a very good free online textbook for Java, and the LearnJavaOnline.org Interactive Java Tutorial is also good.

Matlab

Coursera runs a great course that teaches the basics of Matlab.

Molecular Biology

UCLA has an interactive online tutorial in molecular biology.

Cancer Biology

Several cancer biology animations and videos are available on CancerQuest.

Genomics and Genetics

EMBL-EBI provides a free practical course on the analysis of high-throughput sequencing data as well as another course on functional genomics.

Becoming a bioinformatician takes a lot of hard work, but it’s definitely worth the effort. Check out our article on some of the ways in which bioinformatics can be used. Are there any bioinformaticians out there who can share their experiences? We’d love to hear how you got into your career in bioinformatics in the comments.

References

  1. Vincent AT, Charette SJ. (2015). Who qualifies to be a bioinformatician? Frontiers in Genetics 6:164.
  2. Wu H, Palani A. (2015). ‘Bioinformatics Curriculum Development and Skill Sets for Bioinformaticians’ in 2015 IEEE Frontiers in Education Conference (FIE). IEEE: El Paso, TX.
  3. Welch L, Lewitter F, Schwartz R, Brooksbank C, Radivojac P, Gaeta B, Schneider MV. (2014). Bioinformatics Curriculum Guidelines?: Toward a Definition of Core Competencies, PLOS Computational Biology 10(3): e1003496.

Originally published January 23, 2018. Reviewed and republished February 2021.

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2 Comments

  1. Radha Jaiswal on October 31, 2019 at 11:46 am

    Thanks For Sharing i was looking for information to be a Bioinformatic Scientist. I am a biology major (with a biotech concentration) in undergrad and took a couple of CS classes, along with a introductory bioinformatics course my senior year. this is very helpful for me thanks Again for detail blog



  2. Bioinformatics on December 26, 2018 at 7:34 am

    Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Data intensive, large-scale biological problems are addressed from a computational point of view. It has high scope to build career in it. Thanks for informative article, it is great help for many students. Keep sharing.



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