Chatomics! — The Bioinformatics Newsletter
Why Subscribe?✅ Curated by Tommy Tang, a Director of Bioinformatics with 100K+ followers across LinkedIn, X, and YouTube✅ No fluff—just deep insights and working code examples✅ Trusted by grad students, postdocs, and biotech professionals✅ 100% free
If Claude can do my job in 30 min, what's left?
Hello Bioinformatics lovers, Tommy here. We will talk about AI for bioinformatics today. Half of reddit/bioinformatics is excited. The other half is panicking. The trending threads aren’t about new tools or papers. They’re titled things like “Am I redundant?” Here’s what’s actually happening. The excited half sees AI as a 10x multiplier on tasks that used to take days. AlphaFold 3 predicts proteins, DNA, RNA, and small-molecule complexes in one model. OpenProtein.AI lets biologists engineer...
My 10-year-old analysis is still understandable
Hello Bioinformatics lovers, Tommy here. Ten years ago I wrote down how I processed scRRBS data https://gitlab.com/tangming2005/scRRBS. I still use those notes today. Eight years ago I documented an enhancer-promoter interaction analysis. Still readable. Still makes sense. Meanwhile, I have folders from last quarter named results_final_final2_revised and I have no idea what’s in them. That’s the gap. And it’s the difference between a pipeline you can rerun, a dataset you can reuse and a pile...
AI in pharma: the wrong half is winning
Hello Bioinformatics lovers, Three years ago I wrote that AI hadn't revolutionized drug development. The 2026 update: still hasn't. But the part that's working isn't the part anyone writes articles about. AI for Biology? Here's what I'd revise. Two buckets to categorize AI: AI touching Process — trial ops, statistical programming for FDA submissions, pharmacovigilance. Text and structured data. AI touching Biology — target ID, lead generation, toxicity prediction. Noisy, sparse,...
The question to ask before "integrating" omics
Hello Bioinformatics lovers, Tommy here. Today's newsletter is a little late as I was taking care of the kids in the morning. Multiomics is hot and everyone is talking about it. Let's take an honest view on it. Multiomics is messy Multi-omics integration sounds powerful. RNA-seq, methylation, proteomics — stack them together and unlock deeper biology, right? Not quite. Before you run MOFA2 or DIABLO, there’s one question that decides everything. And most people skip it. The question: shared...
You're not a real biologist
Hello Bioinformatics lovers, Tommy here. I am in Yale today for an event. Hope you enjoy today's newsletter. I am a biologist too "How do people like you ever get last-author papers?" A cell biologist asked Florian Markowetz this during a 2008 job interview. The subtext: you just crunch numbers. You're not a real biologist. Markowetz went on to write one of the most important essays in our field: "All biology is computational biology" (PLOS Biology, 2017). By 2012, a funding panel had called...
The gene that fools every new analyst
Hey Bioinformatics lovers, Tommy here. Everyone once was a beginner, and I made mistakes too. However, the experience is something you gained by making those mistakes. TTN shows up near the top of every cancer exome waterfall plot. If you're new to somatic variant analysis, you'll see it and think you found a driver. TTN is the largest gene in the genome You didn't. TTN encodes titin, the largest human protein at ~34,000 amino acids. The gene has 363 exons. A coding sequence that massive...
I almost sent wrong figures to my collaborators
Hello Bioinformatics lovers, Tommy here. When you read this, I am on my way to New York City for a conference. I am pre-scheduling it at 11:30pm. I have been using Claude Code for a couple of month. I love it and the capbility of coding has been increasing. I am very impressed by the opus 4.6 model. However, just last week, I almost sent a figure with wrong cluster labels to my collaborators made by Claude Code. Watch out! The R code ran. No errors. No warnings. The heatmap looked beautiful....
Every common stat test is the same test
Hello Bioinformatics lovers, Tommy Here. I drove back from Rutgers University last night after a panel discussion on AI and bioinformatics. I am writing this in the early morning:) We talked about a lot on how AI can transform the drug development process and I do see a big potential too. btw, the campus is beautiful. But I then thought: how about the foundations, the basic statistics? Those are still the important things to learn, especially at the age of AI. Let's talk about it. In grad...
AI won't replace you. This will
Hello Bioinformatics lovers, Tommy here. It can be overwhelming with all the advancement of AI. AI won't replace bioinformaticians. But a bioinformatician who uses AI will replace one who doesn't. learn more AI In 2013, when you hit a wall — a confusing error, a method you'd never used — you posted on Biostars and waited. Or you searched for hours and hoped someone had blogged about it. Now you ask Claude or ChatGPT and get a working answer in 30 seconds. That's not magic. That's leverage. I...
Your Machine Learning model learned the noise
Hello Bioinformatics lovers, Tommy Here. 2 Months have past in 2026! Are you learning new skills? Today, we will talk about ML.Your model hit 99% accuracy. Now ask: what did it actually learn? ML models learn the artifacts High accuracy doesn't mean your model learned biology. It might have learned your batch effects, your sequencing center, your hospital's imaging artifacts. Here's a famous example. Researchers trained a model to classify wolves vs. dogs. High accuracy. Then they used LIME...
Why Subscribe?✅ Curated by Tommy Tang, a Director of Bioinformatics with 100K+ followers across LinkedIn, X, and YouTube✅ No fluff—just deep insights and working code examples✅ Trusted by grad students, postdocs, and biotech professionals✅ 100% free