The New Kid! Bioinformatics as an Emerging Science

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It’s tough being the new kid.  They often have trouble finding where they fit within the pre-existing social community.  Over time though, their character shines through, reputation grows and they settle into their niche.  The young field of bioinformatics knows the feeling, straddling the line between biology and computer science.  Although most computational biologists (bioinformaticians) have a background in one of the two sciences, they still have trouble “fitting in” with either group.

Venn Diagram shows the overlap of two well established sciences to form a new field of study.
Venn Diagram shows the overlap of two well established sciences to form a new field of study.

Bioinformatics, also known as computational biology, is the study of biology by exploiting the immense computational power that is available today.  It was a science born out of NEED!  There are approximately 37 trillion cells in the human body.  Do we think a biologist sat around and counted those?  Of course not, that would literally take forever.  There are complex mathematical formulas based on existing data that help us arrive at that number.  Bioinformatics’ crowning achievement thus far occurred about a decade ago when the Human Genome Project was completed (April 2003).  The goal, when funded in 1990, was to sequence the entire human genome.  We learned that there are approximately 30,000 genes and 3.16 billion base pairs in one human genome.   The completion of the HGP ignited a curiosity in scientists all over the world and the birth of “Big Data” just occurred in biology.  A graph from the National Center for Biotechnology Information (NCBI) shows the growth of number of genes sequenced over time and the number of whole genomes sequenced (WGS) over time.  Hidden within those sequences are personalized cancer therapies, disease resistance/predisposition and the key to aging.  We just need computational biologists to unlock those secrets.

Why is Bioinformatics under-appreciated in the scientific community?  The answer is two-fold:  fear and the ability to communicate.  Biologists are scared to trust assumptions, computer models and mathematical formulas that computer scientists create.  Also, computer science programmers aren’t trained in biological methods so they do not understand the biology-speak.  This problem left a NEED for people who are trained as both biologists and computer scientists.

Two experiences from my bioinformatics graduate education highlight the problems perfectly.  I studied biology as an undergraduate, so that is where I feel the most comfortable. However, in bioinformatics, you have to be an expert in both biology AND computer science.  Last year, taking an introductory computer science course (deer in the headlights, complete amateur), the topic of  “global variables” came up and I didn’t understand it at first.  I remember asking a graduate student who taught lab section of the course to help explain and he laughed at me, saying that “if I didn’t understand this topic, I was in the wrong program”.  At first, I was discouraged, and I instantly understood why bioinformatics is so hard to “stick”.  As a biologist, you really have to grind through those introductory weeks, months, years… of learning to program.  The second experience made me feel ashamed of biologists.  In the introductory biology course, there were several computer scientists enrolled.  Every week it was a new question about why adenine base paired with thymine or what the difference between the five prime and three prime end of  a DNA strand was.  Stuff I could recite in my sleep.  I felt myself judging them, but quickly remembered the feeling I had when I was in “their” realm, across campus, in the computer lab.  So, I believe patience will be important for bioinformatics to continue to succeed and thrive as a science.

Bioinformatics is here to stay.  I propose a happy marriage moving forward, as science and technology grow together.  Computer scientists should embrace biologists and be willing to teach them the tricks of the trade, not frown at them when they don’t know how to write a block of code “recursively”.  On the other side of that same coin, biologists should show respect and guide computer scientists down the path of good experimental design, rather than pointing out “obvious” flaws in mathematical formulas.  Studying bioinformatics and computational biology has been one of the most rewarding, eye-opening endeavors in my life.  I look forward to the challenges ahead as well as the chance to educate the next generation of computational biologists.

If you’ve made it this far, you’ve read my FIRST BLOG EVER!  Thank you so much for reading, please leave comments, I’m interested to hear what you have to say.

Kevin Arvai

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