Hello Bioinformatics lovers,

Tommy here. We had two feet snow in Boston. we lost power for 18 hours but I am grateful for that experience.

Back to Bioinformatics.

A hiring manager recently told me something that stopped me cold.

Their biggest challenge isn't finding bioinformaticians who can code. It's finding ones who can talk to biologists.

You can write beautiful Snakemake workflows and optimize DESeq2 parameters in your sleep.

But if you can't explain why you chose those parameters to a biologist standing at your desk—your analysis won't be trusted.

And untrusted analysis doesn't ship.

This is a career-limiting problem.

Biology doesn't follow if-else logic

The same transcription factor can activate genes in one cell type and repress them in another.

A protein's function shifts with culture conditions or subcellular localization. You can't just look up the answer—you need intuition for how messy biology actually is.

Rigid, engineering-style thinking breaks down fast here. If you can't navigate that messiness in conversation with collaborators, you'll struggle to produce analyses that answer their real questions.

The path depends on where you started

If you came from CS: Your challenge is biology. Start with the fundamentals—what a promoter does, why batch effects wreck your analysis, how experiments actually work from hypothesis to sequencing.

You don't need a biology degree, but you need enough to interpret your results in biological context.

If you came from biology: You have an enormous advantage. You already understand experimental design, biological variability, and why that one sample looks weird.

That intuition is incredibly hard to teach. Data analysis skills? Those you can learn. I went from not being able to open a 2 GB file to leading computational biology teams. Your biological instinct is the harder thing to acquire, and you already have it.

Try this

Pick one recent analysis and explain it to a non-computational colleague in under two minutes.

No jargon. Just: what did you do, what did you find, and why should they care?

If you stumble, that's your growth edge. And it's worth sharpening.

Happy Learning!

Tommy aka crazyhottommy

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. other useful daily posts from my Linkedin https://www.linkedin.com/in/%F0%9F%8E%AF-ming-tommy-tang-40650014/recent-activity/all/​

Stay awesome!

PPS: