You’ve likely seen the meme that puts your brain to the test by challenging you to quickly make sense of the following scrambled letters:

          fi yuo cna raed this

It’s also likely that you aced the test. The average human brain, always seeking order and meaning, can typically sort the letters into the real words: If you can read this.

The same is true of syntax:

          What i if told you  

          You the read first line wrong

          Same the with second

          And also the third!

While you likely felt a wave of pride at your ability to decipher the words or phrases, chances are you’ve never attempted to decipher millions or even billions of letters at once. For example, most people would become overwhelmed if asked to decipher this:

sessecorp lacigolob laitnademunf gniyredlnu steercs eht gnirevocnu yB, nac ew dnif evitavonni sehcaorppa ot esongaid, taert, dna tneverp esaesid. lanoitadnuoF hcraeser si erehw seruc nigeb. * 

But when it comes to biological research, that’s the challenge posed by experiments that can generate billions of pieces of data. When scientists sequence DNA or map where proteins bind across the genome, they’re not looking at a few data points. They’re looking at massive datasets that are impossible to interpret by eye or even with traditional technologies and computers.

This is where bioinformatics becomes helpful. Bioinformatics is what happens when biology meets computing — it’s a field that helps organize, analyze, and interpret massive amounts of biological data in ways humans cannot. Inside DNA for example, it combines biology, coding, math, and statistics to find meaningful patterns that would remain otherwise hidden.

With recent advances in artificial intelligence, the field is becoming even more important. Biologists now wield powerful new computational tools for tackling the large amounts of data organized by bioinformatics. AI can learn patterns and make predictions more quickly and accurately than a human or a traditional statistical model.

Think of it like this:

Bioinformatics asks the most complex biological questions — and AI is one of the tools we can use to help answer them.

Without bioinformatics, we’d just have mountains of raw data.

But thanks to the field, we can turn that data into real discovery.