Hello Bioinformatics lovers,

Tommy here. I was trained in a wet lab.

And we all had the same experience:

When your PI says "make 10 RT-qPCR reactions," you make 12.

Not because anyone told you to. Because you've lost volume to pipetting one too many times. You just know.

That instinct — the automatic adjustment born from past failures — is what separates a beginner from a practiced scientist.

And bioinformatics has its own version of it.

The knowledge nobody writes down

Bioinformatics mastery isn't about learning one more tool. It's about the hundreds of small habits you accumulate over years.

-habits that no textbook covers because they only crystallize through experience.

Here's what I mean.

In the wet lab, you learn to plate samples following the tip box order — left to right, row by row — so you never lose track of which well you're in.

It's not in the protocol. It's earned knowledge from staring at a half-empty plate wondering where you left off.

Bioinformatics has the same kind of earned knowledge.

You learn to use !$ in bash instead of retyping the filename you just referenced.

You learn to never run a destructive command like rm * without pausing.

You learn to save scripts and stop overwriting results without backups.

These aren't year-one skills. They're year-three, year-five, year-ten skills.

The paranoia that protects you

Experienced bioinformaticians develop a productive paranoia. You don't trust data at face value.

You run PCA on your samples and actually look at the plot. If your control and knockdown samples cluster together instead of separating? Something went wrong — a sample swap, a labeling error, a failed experiment.

That PCA plot just saved you weeks of chasing phantom results.

The same instinct applies to variant calling. A low allele frequency variant might not be real — it could be PCR amplification bias or a mapping artifact.

Mutation calls are only as good as your filters. And nothing replaces pulling up that region in IGV and checking it with your own eyes.

This is the real work of bioinformatics: not running pipelines, but questioning every output.

Pattern → function → sanity

You also learn to stop doing things manually. When you catch yourself writing the same code block for the third time, you turn it into a function.

Then you run that function on 10 samples. Then 100. Then 1,000.

That discipline — pattern recognition followed by automation — is what scales your work without scaling your errors.

Does this result make biological sense?

If I could distill years of experience into one habit, it's this: pause before you celebrate a result and ask whether it makes biological sense.

A beautiful volcano plot means nothing if the top hit is a gene that has no business being differentially expressed in your system. A perfectly formatted VCF file means nothing if you haven't sanity-checked the calls.

Bioinformatics isn't one pipeline.

It's data plus curiosity plus paranoia. It's pattern matching across chaos.

The real skill is invisible

Experience in this field isn't flashy. It's quiet. It's the instinct to pause, double-check, and rerun before you report a finding. It's making 12 reactions when you need 10.

Small habits build big reliability. And that's what makes a real bioinformatician.

What's your hard-won lesson — the thing you know now that you wish someone had told you on day one?

Hit reply and tell me. I read every response.

Happy Learning!

Tommy aka. crazyhottommy

I am going to attach an insipirational quote in the future emails. Hope you like it as I do!

PS:

If you want to learn Bioinformatics, there are four 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/​
4. Read my last week's daily Linkedin post.​

Stay awesome!

PPS: