Bioinformatics is not magic. Even though it might seem that way, behind every result there’s a set of tools, knowledge, and people working to translate mountains of biological data into something useful and meaningful.
I recently watched a seminar by Dr. César Augusto Pot Hernández from the Instituto de Fisiología Celular at UNAM (IFC-UNAM), where he clearly explained what bioinformatics really does in a university setting—where it’s taught, researched, shared, and used to support other scientific work.
Here’s a concise summary in 7 points:
What does bioinformatics do?
1. Translates raw data into understandable representations.
From genome readings to cellular images, bioinformatics helps organize, visualize, and explore data. What are we seeing? What should we see?
2. Assigns biological meaning to findings.
A result is not useful unless it can be interpreted biologically. Why is this gene overexpressed? What does this pattern mean?
3. Develops tools and models.
It’s not just about using software—bioinformaticians often build it. Predictive models, automated pipelines, data exploration interfaces. It’s computational science serving biology.
4. Provides scientific support to other areas.
Many biologists don’t code directly. That’s where bioinformatics comes in as an interdisciplinary partner: clear questions, computational answers.
5. Engages in teaching and training.
Knowing how to do the work isn’t enough. Bioinformatics also means teaching others. At IFC-UNAM, students are trained from fundamentals to real-world applications.
6. Relies on specialized computing infrastructure.
Servers, clusters, workstations—processing genomic or cellular image data requires far more than a regular laptop. Infrastructure matters.
7. Operates within an ecosystem of scientific services.
At places like IFC-UNAM, bioinformatics isn’t an isolated island. It collaborates with molecular biology, microscopy, structural modeling, and more. It’s part of a larger gear.
A field for those who ask, model, and connect
Dr. Pot emphasized that bioinformatics requires more than programming skills—it also needs scientific sensitivity, good questions, and teamwork. It’s not magic: it’s knowledge, care, and purpose-driven code.
🦠 If you’re curious about the intersection of computation and life, this is a field where there’s still so much to build.
Whether you’re into data science, biology, or software—maybe it’s time to look into a microscope… with a script in hand.