Ryan Dale, PhD
What is bioinformatics?
Bioinformatics is a field of science that uses computational methods and different computer programs to store, organize, analyze, and understand biological data from many sources, including research studies, clinical trials, scientific journals, patient medical records, and biospecimens. Sometimes, bioinformatics is referred to as computational biology.
NICHD fellows gathered on July 17 to learn from Ryan Dale, PhD, who directs the NICHD Bioinformatics and Scientific Programming Core (BSPC), as he shared his experience starting as a marine biology researcher and moving into bioinformatics while completing his doctoral studies. His talk, which was part of the NICHD Careers, Challenges, and Connections series, included advice for NICHD scientists on ways to learn more about bioinformatics. Dr. Dale broke down his guidance into six simple points, which are summarized below:
#1: A formal background or bioinformatics degree is not required.
Many practicing bioinformaticians have not taken bioinformatics, programming, or computer science classes. Plus, formal classes might not exist for every application. The internet has plenty of free, high-quality content that can be effectively utilized.
#2: Learning bioinformatics is a lot like learning to play piano.
Piano playing and bioinformatics contain technical and creative components, and time must be spent practicing both. In addition, much like learning to play the piano (or any instrument, or even any language), the learning process for bioinformatics training will be slow at the beginning and will require lots of practice in between lessons.
#3: Bioinformatics lessons can be highly effective.
In addition to short-term, intensive workshops, bioinformatics lessons can accelerate learning more efficiently. Instead of personal one-on-one lessons like for piano, online tutorials can be used as lessons for bioinformatics training. Most importantly, scientists should make the time to practice bioinformatics skills on their own in between lessons. It might not be reasonable to expect progress after completing a workshop and then setting bioinformatics aside until you “need it.”
#4: Persistence is key.
To become proficient at bioinformatics, you will fail a lot; and then you will learn through the process of fixing your failures. Often, not everything is spelled out in online resources or textbooks. Necessary information may need to be more creatively accessed, for example, by combining information from multiple resources or by adapting one resource for a slightly different application. Debugging and troubleshooting is greater than 80% of coding, but if you enjoy puzzles, you will have a lot of fun.
#5: Learn how to learn.
Bioinformatics is always evolving. Fellows can take many steps to continue learning bioinformatics, including:
- Reading tool documentation
- Using the right search terms to fill in any gaps in your current understanding of a language or process
- Critically evaluating answers from online coding forums, for example from StackOverflow and Biostars, before using them
- Deciphering methods from papers
- Reading other people’s code to understand its function
#6 Time to practice is the limiting factor.
Practicing bioinformatics only when you go home after a full day in lab will not be very effective. Discuss a training plan with your advisor to establish expectations about balancing bioinformatics training and other lab responsibilities.
If you’d like to learn more, visit the BSPC Training website, where you’ll find various tutorials to get you started, including information on Python, R, and RNA-Seq. Dr. Dale encourages any fellows who are considering bioinformatics training to access and use this resource.
Want to learn more?
Check out some of these NIH bioinformatics resources
- NICHD Bioinformatics and Scientific Programming Core
- NICHD Biostatistics and Bioinformatics Branch
- NIH Bioinformatics Support Program
- NIH Bioinformatics Scientific Interest Group
- NIH Intramural Research Program Scientific Focus Area – Computational Biology
- NIH Library Bioinformatics Classes
- High-performance Computing at NIH
- The Foundation for the Advanced Education in the Sciences Bioinformatics and Data Science courses