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Director of bioinformatics at AstraZeneca. subscribe to my youtube channel @chatomics. On my way to helping 1 million people learn bioinformatics. Educator, Biotech, single cell. Also talks about leadership. tommytang.bio.link
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10/ AI gives you speed. You bring the judgment.
Double-check its code. Validate its logic. Ask better questions.
The future belongs to the curious--especially those who type well.
9/ Ask AI to:
- Explain PCA vs UMAP
- Write a bash loop
- Compare ChIP-seq vs ATAC-seq
- Draft a Seurat filtering function
Then verify everything it gives you.
8/ Will AI replace biologists? No.
But if you're a biologist who doesn't use AI, you're already falling behind.
It's never been easier to learn genomics, statistics, or scripting.
7/ These are the types of questions AI handles well.
Quickly. Clearly. Not perfectly--but better than flying blind.
6/ Another question: why is only 0.1% of ChIP-seq input used?
Short answer: input DNA is plentiful. ChIP DNA is scarce--you're only pulling down what's bound to the protein of interest.
AI explained this in 10 seconds.
5/ Someone asked me: why calculate the TSS enrichment score for ATAC-seq?
Years ago, I'd dig through papers for hours.
Now I ask AI to explain it simply, then go deeper myself.
4/ Even as an experienced bioinformatician, I still use AI daily.
Why? Because it helps me think faster, not lazier.
3/ Now? You ask ChatGPT, Claude, or Gemini.
You get a decent answer in seconds.
That's not magic. That's leverage.
2/ In 2013, if you had a problem, you went to Biostars or StackOverflow.
You waited days. Or searched for hours.
1/ AI won't replace you.
But a biologist who uses AI will.
Especially in bioinformatics, where the questions never stop coming.
Immunosuppressive mechanisms and therapeutic interventions shaping glioblastoma immunity www.nature.com/articles/s4...
02.03.2026 15:15 — 👍 2 🔁 0 💬 0 📌 0
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5. 42basepairs 42basepairs.com/
02.03.2026 14:45 — 👍 2 🔁 0 💬 1 📌 0
4. Intervene: a tool for intersection and visualization of multiple gene or genomic region sets
bitbucket.org/CBGR/interv...
3. The goal of **g(r)osling** is to help you build interactive genomics visualizations with [Gosling](github.com/gosling-lan...). This package uses [reticulate](rstudio.github.io/reticulate/) to provide an interface to the [Gos](github.com/gosling-lan...) Python package.
02.03.2026 14:45 — 👍 3 🔁 0 💬 1 📌 0
2. plotgardener is a genomic data visualization package for R. Using `grid` graphics, `plotgardener` empowers users to programmatically and flexibly generate multi-panel figures
github.com/PhanstielLa...
I used that to plot single-cell ATACseq tracks github.com/crazyhottom..., more examples rpubs.com/crazyhottom...
02.03.2026 14:45 — 👍 2 🔁 0 💬 1 📌 0
5 tools to visualize genomic datasets 🧵
1. Karyoploter bernatgel.github.io/karyoploter...
A pan-cancer compendium of 1,294 plasma cell-free DNA methylomes and fragmentomes enabling multicancer detection www.nature.com/articles/s4...
01.03.2026 15:15 — 👍 7 🔁 2 💬 0 📌 0
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10. whimsical.com/
01.03.2026 14:45 — 👍 0 🔁 0 💬 1 📌 09. Latex www.baeldung.com/cs/latex-fl... if you are geeky
01.03.2026 14:45 — 👍 0 🔁 0 💬 1 📌 08. Lucidchart www.lucidchart.com/pages/ very similar to draw.io
01.03.2026 14:45 — 👍 0 🔁 0 💬 2 📌 07. DiagrammeR if you want to play with R rich-iannone.github.io/DiagrammeR/
01.03.2026 14:45 — 👍 0 🔁 0 💬 1 📌 06. Inkscape github.com/fredhutchio... I use it to make figures (it is free)
01.03.2026 14:45 — 👍 0 🔁 0 💬 1 📌 05. draw.io
01.03.2026 14:45 — 👍 0 🔁 0 💬 1 📌 04. Miro miro.com/aq/ps/flowc...
01.03.2026 14:45 — 👍 0 🔁 0 💬 1 📌 03. Adobe illustrator
01.03.2026 14:45 — 👍 0 🔁 0 💬 1 📌 02. Figma www.figma.com/templates/f... recently bought by Adobe
01.03.2026 14:45 — 👍 0 🔁 0 💬 1 📌 0