THE CODE OF LIFE How Bioinformatics changes our lives

“In this fast-evolving genomics era, if Sri Lanka hopes to overcome its unique health and economic challenges while remaining scientifically competitive, this strategy of investing in local talent to solve local problems is exactly what I believe it should emulate.” 

“In June 2000, when the first draft sequence of the human genome was announced, the cost of sequencing those 3 billion letters hovered near $100 million... As I write this in mid-2026, the price tag has reached the coveted $100.”  

“Investing in bioinformatics can also have indirect economic benefits by retaining local talent and creating alternative job opportunities for graduates entering an over-saturated IT job market.” 

“What none of us grasped at the time was that a quiet revolution was already underway; bioinformatics was rapidly moving from the fringes of biology to its forefront, a move that would soon change economies and redefine scientific competitiveness around the world.” 

Bioinformatics has rapidly evolved from a niche discipline into a global economic and scientific powerhouse. As DNA sequencing costs plummet, Sri Lanka faces a critical juncture. The country can no longer afford to rely on foreign research to solve domestic crises like Chronic Kidney Disease. By investing in local talent, training its life scientists to code, and tapping into its abundant IT workforce, Sri Lanka can protect its scientific sovereignty, combat “parachute science,” and unlock new, high-impact career pathways for its youth.

A little over a decade ago, I was first introduced to bioinformatics, the field of science that uses computational tools to store and analyze large amounts of biological data. I had just arrived in the US from Sri Lanka, eager to pursue a PhD in Biological Sciences. Not long after my arrival, my adviser pointed to a large computer sitting in the corner of our lab and told me that a part of my dissertation would involve handling over 500 gigabytes of sequencing data that would soon arrive. He unhelpfully added that the data was generated from a “Next-Generation Sequencing” experiment.   

As a trained bench scientist, I was instantly intimidated by the magnitude of the task. And then there was the imposing Linux machine that stood blinking at me with its cursor, silently judging my inability to code. That first semester, I avoided that computer the way a Sri Lankan would turn their nose up at a bland curry; my schedule overflowed with classes and long hours at the bench. But soon, like many graduate students in the life sciences at the time, I began to realize that learning to code was unavoidable if I wanted to succeed. What none of us grasped at the time was that a quiet revolution was already underway; bioinformatics was rapidly moving from the fringes of biology to its forefront, a move that would soon change economies and redefine scientific competitiveness around the world.   

By the time I first encountered bioinformatics, it had been around for several decades. Still, the field received its biggest boost from the Human Genome Project, a massive multi-institutional undertaking that began in the early 1990s to decode the human genome. The project led to many scientific advances, but none was more transformative than Next-Generation Sequencing (NGS). Traditional sequencing methods read small sections of DNA at a time – often a slow, laborious process with limited scalability. In comparison, NGS could read millions of tiny DNA fragments at the same time, allowing massive amounts of DNA to be decoded at a record pace.

Each year, as we watched in awe, a newer, more advanced NGS platform seemed to replace the old, causing sequencing costs to dramatically drop. In June 2000, when the first draft sequence of the human genome was announced, the cost of sequencing those 3 billion letters hovered near $100 million. A decade or so later, as I waited for my 500 gigabyte dataset to arrive, the same cost had dropped to about $1000. As I write this in mid-2026, the price tag has reached the coveted $100. This decline in sequencing costs unleashed an influx of biological data that needed to be stored, analyzed, and interpreted. Bioinformatics simply had to keep up.

Generating sequencing data was no longer a problem, but storing and analyzing it was. To tackle this, developed nations invested heavily in building computational infrastructure. In the US, the National Institutes of Health (NIH) poured millions of dollars into building public repositories like the Sequence Read Archive (SRA). It has since become an invaluable tool for genomics research. The NIH also funded university-operated High-Performance Computing (HPC) centers that could efficiently manage workloads and allow multiple users to analyze data at the same time. Well into my first year of graduate school, when I finally sat down to analyze my dataset, I realized that the Linux machine itself provided a gateway into one of these very same HPC centers.   

Investing heavily in sophisticated computational infrastructure was not an option for forward-thinking developing countries. They instead focused on training local talent and developing strategies that target diseases plaguing local communities. One such initiative is the H3Africa program, a pan-African network of laboratories created to tackle disease susceptibility in African populations. H3ABioNet, its bioinformatics arm, trains hundreds of local scientists across 16 countries in Africa each year. In this fast-evolving genomics era, if Sri Lanka hopes to overcome its unique health and economic challenges while remaining scientifically competitive, this strategy of investing in local talent to solve local problems is exactly what I believe it should emulate.   

During my undergraduate years in Sri Lanka, my exposure to bioinformatics was limited; the word ‘bioinformatics’ did not yet exist in my vocabulary. At the time, opportunities to study bioinformatics were equally scarce. Much has changed since then. A small number of degree programs entirely dedicated to this discipline have emerged. Private companies have also started to organize workshops to train aspiring bioinformaticians. While these efforts clearly show progress, they remain concentrated within a handful of institutions, primarily within Colombo. Unfortunately, this means that many Sri Lankan students in life sciences may still graduate with limited exposure to bioinformatics, unaware of its potential to shape their careers and even the economy.   

The potential of bioinformatics extends far beyond its often-touted applications in human health. From a human health perspective, countries that invested early in bioinformatics have continued to reap the benefits. These same countries have enjoyed early access to vaccines, improved disease diagnostic methods, and advanced therapies for diseases such as cancer. Sri Lanka can also benefit from targeted investments in bioinformatics, with special focus on diseases that affect local populations such as the chronic kidney disease (CKD) that continues to mysteriously afflict the north central province.

What genetic predispositions or environmental conditions might cause these hotspots of disease? If we fail to look for these answers ourselves, well-funded foreign researchers will gladly do it for us. This scenario–termed “parachute science”–describes how scientists from wealthy nations descend on developing countries, conduct fieldwork, collect data, and leave without any significant contributions to local communities. At least in the life sciences disciplines, building a competent bioinformatics workforce with deep knowledge of local communities will help dismantle attempts at parachute science.   

Investing in bioinformatics can also have indirect economic benefits by retaining local talent and creating alternative job opportunities for graduates entering an over-saturated IT job market. Bioinformatics needs software engineers, cloud architects, developers, and more recently, machine learning experts. Sri Lanka has no shortage of individuals trained in these disciplines, but few job opportunities exist locally. For these skilled professionals, bioinformatics can offer opportunities to do impactful work and achieve fulfilling careers.   

By the time I entered my second year of graduate school, my relationship with the Linux machine had drastically changed. I no longer avoided it – I was obsessed with it. Every time I gave it a few instructions in code, it would unlock more secrets about the genome I was studying. This would lead to more intriguing questions that I would sit down to tackle again the next day. As fascinated as I was by the Linux machine, it took me a few more years to consider pursuing a career in bioinformatics. I was well into my postdoctoral work at the time – trudging along Alaskan mountains scoping the endless tundra for tiny mosses – when the thought suddenly struck me. What I most looked forward to when I returned to the lab was not the long hours at the bench but the time I would spend at the computer, unraveling the mysteries of those fast-changing Arctic ecosystems. Looking back now, I could not be happier about that choice; bioinformatics has provided me with many opportunities to do impactful, fulfilling work. I was glad I made that imposing Linux machine my friend.

Dr. Chathurani Ranathunge is a Sri Lankan computational biologist based in the United States. She holds a PhD in Biological Sciences from Mississippi State University and a BSc in Agriculture with a specialization in Biotechnology from Wayamba University of Sri Lanka.