Hello Bioinformatics lovers,

I just crossed 50K followers on LinkedIn!

Hooray! I hadn't realized that so many people are interested in Bioinformatics.

To celebrate this, today, I am going to talk about:

Regular Expression!

​

Messy data is the rule, not the exception, in bioinformatics.

And yet, most wet lab scientists—and even many computational ones—don’t realize that the difference between chaos and clarity often comes down to one tool: regular expressions (regex).

Regex is how you tame the mess. It’s how you get your datasets to talk to each other when nothing else works.

Let’s walk through why it matters—and how you can use it.

Problem 1: Mismatched Labels​
Dataset one: MDA-MB-231​
Dataset two: MDAMB231

Same cell line. Different spelling. You can’t merge them as-is.

In R:

str_replace("MDA-MB-231", "-", "")
# Result → MDAMB231
​

Simple enough—but what happens when it’s not just dashes?

Problem 2: A Jungle of Characters​
Now it’s dashes, underscores, and slashes—everywhere.

str_replace_all("MDA-MB_231/Clone", "[-_/]", "")
# Result → MDAMB231Clone
​

The magic is in [-_/].

This tiny regex says: find any dash, underscore, or slash—and wipe it out.
One pattern. Thousands of fixes.

Problem 3: The ENSEMBL ID Headache​
Every bioinformatician has seen this:

ENSG00000141510.15

That .15 is just a version number. You don’t want it in your analysis.

Regex saves you again:

str_replace("ENSG00000141510.15", "\.[0-9]+", "")
# Result → ENSG00000141510
​

Breakdown:

• \. = literal dot
• [0-9]+ = one or more digits
  Together, it matches .15, .3, .999—anything.

And when you apply it across a vector:

str_replace(ensembl_ids, "\.[0-9]+", "")
​

Every version number disappears in one shot.

Problem 4: Filtering IDs​
Want to keep only those that start with ENSG?

str_subset(ensembl_ids, "^ENSG")
​

The ^ anchors to the start of the string. That’s regex precision.

Problem 5: Weird Characters from File Imports​
Ever seen invisible characters break your scripts? Regex wipes them clean.

str_replace_all(text_column, "[^\x00-\x7F]", "")
​

This removes all non-ASCII characters. Suddenly, your files behave again.

Why This Matters

Regex looks small. Just symbols and brackets.
But it compounds.

One pattern can save hours of manual cleanup.
One pattern can prevent a mistake that would throw off an entire project.
One pattern can make merging thousands of samples possible.

That’s why regex is not just a trick—it’s a superpower.

Something fun: this is the regex to match a valid email address:

Key takeaways:

• Regex cleans messy data fast.
• It works on gene IDs, labels, metadata—anything text-based.
• Pair it with stringr for clean, reproducible code.

Action items:

• Learn symbols like [], +, *, ^, $.
• Use str_replace_all() often.
• Next time your dataset looks unmergeable, try regex first.

Bioinformatics is full of messy data. Regex is how you fight back.
Master it—and your future self will thank you.

Other posts that you may find helpful:

1. ​Ten Quick Tips for Avoiding Pitfalls in Multi-Omics Data Integration Analyses.
2. Making a heatmap is an essential skill for a bioinformatician. But you probably do not understand heatmap. 7 reading resources to understand heatmap​
3. Bioinformaticians and wet biologists working together. Here’s why it matters. ​
4. 🧵Bioinformatics evolves fast. New tech. New data. New analysis. But here's how to stay grounded and not get overwhelmed.
5. The person you will be in 5 years depends on:
6. 🧵 Bioinformaticians: Drowning in multiple projects?​
7. If you're doing bioinformatics without Git, you're gambling with your research.
8. Bash scripting quirks & safety tips ​
9. One of the best free stats books for life science with R
10. ​SVD & PCA: The hidden math shaping bioinformatics discoveries

Happy Learning!

Tommy

PS:

If you want to learn Bioinformatics, there are other ways that I can help:

1. My free YouTube Chatomics channel, make sure you subscribe to it.
2. I have many resources collected on my github here.
3. I have been writing blog posts for over 10 years https://divingintogeneticsandgenomics.com/​

Stay awesome!