Computational Biology: The Key to Immortality
Computational Biology is an emerging field with immense potential. But what exactly is it?
Introduction
Computational Biology is an up-and-coming field with the potential to rapidly accelerate vaccines and cures, develop general-purpose drugs, and fight the antibiotic resistance crisis. But what exactly is it, and how does it work?
To understand computational biology, you need to understand data. For a while now, large amounts of data have been fed into large AI algorithms (such as ChatGPT) to simulate intelligence or to solve problems. The data can come from scraping the internet, scientific experiments, or anywhere else. However, it wasn’t until recently (around 5–6 years ago) that individuals used these datasets to analyze and understand biological systems.
Essentially, computational biology is a field where data collected from experimentation is fed to deep neural networks that try to determine underlying patterns. Even though the area is new, it has already had some incredible breakthroughs that will almost certainly save lives. Here are a few big ones:
Protein Folding (Alpha-Fold 2, Rose TTA Fold, and others)
In 2020, Alpha-Fold 2 made breaking news by being the first AI to successfully pass CASP (a test to determine an AI’s accuracy). This was significant for two reasons. First, it showed that AI could understand biological systems that humans will never process independently. Second, simulating protein folding can accelerate drug development immensely by letting researchers custom-tailor proteins and enzymes to deal with viruses or other afflictions.
Alpha-Fold 2 has one flaw, though: the considerable computing power needed to run it. So, Rose TTA Fold entered the field as an alternative with lower accuracy but much lower computing power. Now, most researchers can access folding simulations while designing vaccinations or cures.
DNA Sequencing
DNA sequencing has been done for a long time, but recent innovation means it is at its fastest pace yet. Patients can now get nearly their entire genome sequenced in under 10 hours, which may sound like a lot but is incredible given the three gigabytes of data that need to be extracted and stored.
Sequencing has many uses, as it reveals what conditions an individual may be predisposed to. Additionally, it could provide the necessary information to cure genetically passed disorders.
Biomedical Image Analysis
While Biomedical Image Analysis is likely the least developed sector I will discuss, it still has immense potential. Currently, most doctors have to analyze MRI, CT, and ultrasound (and others) scans by eye, leading to many overlooked problems and multiple errors. However, researchers are now supplementing this process with computers, which will dramatically increase the speed and efficiency of the process. Doctors will be spared a lot of work when it fully develops, and many people will finally get accurate test results.
Conclusion
While we could discuss many more computational biology breakthroughs, I only discussed three for brevity. The field still needs to mature, and interested individuals have immense potential to make an impact. Personally, I find computational biology interesting because it could lead to a cure for many autoimmune disorders and allergies, something I struggle with. Keep in mind, it could save lives (and make money).