"AlphaFold solved biology" is the most expensive misunderstanding in tech right now. What AlphaFold actually solved: protein structure prediction. What that means for drug development: less than the marketing suggests. Here is the part that gets lost in the headlines.

A copy number of 4 in DepMap does not mean what you think it means. Half the analyses I see treat OmicsCNGene.csv like it contains absolute copy number. It does not.

Are you ready to level up your bioinformatics skills? Let’s talk about repetition—a key concept that can save you hours in real-world data analysis. 🧬

You hear the term “hyperparameter” all the time in machine learning. But do you really know what it means—and why it matters? Let’s break it down.

for RNAseq, what does removeBatchEffect() function do in limma? I see a bioinformatician run it before differential expression testing, then wonder why their results look too good.

You inherit someone else’s bioinformatics code. No comments. No structure. Variable names like x1, foo, temp2. And now it’s your problem. Let’s talk about that experience—and how to do better.

Daily wisdom. Do something with AI practically. too much noise there if you do not try it yourself. do not just watch as an outsider daily-quote-app-mu.vercel.app/

My Nextflow Summit talk on Reproducible Bioinformatics is now on Youtube. www.youtube.com/watch?v=c9Q... Thanks again for the invitation! Slides can be found here divingintogeneticsandgenomics.com/talk/2026-n...

Bioinformatics is more about biology and code. It's shells and sessions, exports and environments. Ever been confused by “login shell” vs “interactive shell”? This thread is for you. 🧵

1/ Doing bioinformatics is not just crunching numbers. It’s running experiments—just like a wet lab scientist does. But with code.

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My next newsletter "MCF7 or MCF-7? Your data doesn't care" is coming today. Subscribe to get it and stay in the loop on everything I'm creating. divingintogeneticsandgenomics.kit.com/profile

Robust integration of single-cell datasets with imbalanced modality composition www.nature.com/articles/s4...

Your cell line sequencing data isn’t mapping well? Before blaming the aligner—check if you're sequencing bacteria instead of human. Let’s talk about mycoplasma contamination.

You swear at the code. You’re sure the computer’s being stupid. But it’s not the computer. It never was. 🧵

Polars: Blazingly Fast DataFrame Library docs.pola.rs/

“How long will the bioinformatics analysis take?” If you’ve ever been asked that… you know the answer: It depends. Here’s why: 🧵

Why are there intronic reads in your bulk RNA-seq data? You're not alone—it's common, and the reasons are more layered than you think. Let’s break it down. 🧵

review: Epithelial-to-mesenchymal transition(EMT) as a central driver of tumor cell plasticity www.nature.com/articles/s4...

Ever wondered why analyzing RNA-seq data feels like walking through a fog with 20,000 dimensions? Let’s talk about the curse of dimensionality in bioinformatics—and why it’s not just a math problem, it’s a biological one. 🧵

Your code keeps failing. You're knee-deep in error messages. But sometimes, the fix is so simple—it feels like magic. 🧵

One of the best Claude Code feature is auto mode. It is a classifier that decides which permission prompts you actually need to see. Safe reads and routine commands run without interrupting you. Anything that looks risky still gets blocked and surfaced for approval.

You’re analyzing 10x Genomics single-cell RNA-seq and notice lots of intronic reads. Wait—wasn’t this a 3′ UMI-based assay for mature mRNA? Let’s unpack why introns show up—and why they matter. 🧵

You think two genes are correlated. But what if there's a third gene pulling the strings? Let’s talk about partial correlation in bioinformatics.

Nature Protocols: A versatile toolkit for drug metabolism studies with GNPS2: from drug development to clinical monitoring www.nature.com/articles/s4...

Claude Code's /ultraplan is one of the AI feature in a while that actually changed my workflow instead of just speeding it up. btw, I always use /plan for a new task. /ultraplan is different.

Bioinformatics isn’t hard because of code (with codex and Claude Code, you can write code much faster). It’s hard because of decisions. Thousands of tiny choices that shape your results. Here's a thread.

Claude Code shipped /ultrareview and almost nobody is talking about what's actually new about it. It's not "AI reviews your code." We had that.

1/ “Deep neural networks (DNN) are just glorified linear models.” You’ve probably heard this. But let’s be honest: it’s both true… and completely wrong.

Sample swaps are the silent killer in bioinformatics. Your results look clean—but are you sure you're analyzing the right samples?

High-content CRISPR activation screens identify synthetically lethal RNA-based mechanisms to sensitize cancer cells to targeted T cell cytotoxicity www.nature.com/articles/s4...

1/ You used autoplot() for PCA and your PC1 and PC2 axes look weird? Don’t blame your data—blame blind trust. Let me explain.

1/ How many hours do bioinformaticians lose matching sample IDs across assays? Too many. And it’s avoidable. Let’s talk about why this happens—and how to stop it.

Dual targeting of PI3Kγ and STING overcomes regulatory B cell- and myeloid cell-driven immune suppression in pancreatic cancer www.nature.com/articles/s4...

1/ You have a clear question: Is gene A and gene B co-expressed in my cell type of interest? You feel ready. You have single-cell data.

1/ AI won't replace you. But a biologist using AI will. Especially in bioinformatics, where the questions never stop coming.

"Biology is 10+ orders of magnitude more sophisticated than transistors." That's Joseph Jacks's framing on X this month, and it's becoming a dominant thread among AI-pilled tech founders. Here's why it matters if you work in bio.

Bioinformatics is hard before you even write a single line of code. Here's why. 1/ You haven’t started your DNA-seq analysis. You haven’t aligned a read. And yet you’ve already hit a wall. Which human genome to use?

1/ A year into bioinformatics, your code starts to work. But that’s also when it gets dangerous. Because now you can fool yourself.

Spatial-aware detection of copy number alterations from spatial transcriptomics using SpaCNA www.nature.com/articles/s4...

7 FREE Books to learn data science 🧵 👇 1. Data science: A first introduction datasciencebook.ca/

🧵 You’re not behind in bioinformatics. The field just evolves faster than anyone can follow. 1/ It’s not you. Bioinformatics evolves too fast. And not just from new algorithms— But from how fast technology itself changes.

Charting spatial ligand-target activity using Renoir www.nature.com/articles/s4... github repo github.com/Zafar-Lab/R...

"Am I redundant?". The bioinformatics community is having an identity crisis. r/bioinformatics had 4,612 upvotes across 13 threads in the last 30 days. The most upvoted threads aren't about new tools or papers. They're titled things like "Am I redundant?"

The Hidden Chaos Behind Beautiful Bioinformatics Figures 1/15 You only see the final beautiful figure in that bioinformatics paper. But behind every clean heatmap lies a storm of trials, errors, and late-night debugging sessions.

chatomics! 9 videos teaching you how to recreate Figure 1 step by step from a genomics paper with ChIP-seq data have been finally done. Watch here www.youtube.com/watch?v=-UK...

1/ Bioinformatics isn't just code. It’s intuition. You run the stats, but you feel when something’s wrong. That feeling is a clue.

1/"I have a presentation tomorrow." If you've ever collaborated with wet lab scientists as a bioinformatician… you’ve heard this. And died inside a little.

You just downloaded a 20GB enhancer x sample matrix. One problem: the first column header is missing. 1/ You stare at a giant matrix. Rows = enhancers. Columns = samples. But there’s no header for the enhancer ID column.

Now you are a real bioinformatician after you executed this command: rm -rf /* DO NOT DO IT :)