In a collaboration with researchers at Notre Dame and NYU, Tesorai Search identified 136% more high-confidence peptide identifications than standard search engines. Resulting analysis contributed to a pan-cancer atlas of 28,446 tumor-specific antigens. Publication: www.biorxiv.org/content/10.1...

In immunopeptidomics, a missed peptide isn't just another data point. It could be a tumor-specific antigen that never gets investigated. That's why sensitivity matters.

Some discoveries start with a single missed peptide. More peptide identifications don't just improve a metric—they can reveal biology that would otherwise remain hidden. 👇

Many analysis workflows require exporting differential expression results into another tool for pathway analysis. With Tesorai, differential expression and GO enrichment happen in the same workflow—so you can move from proteins to biology without leaving the platform.

GO enrichment groups proteins into biological functions and pathways. Instead of looking at individual proteins, you can begin identifying the biological processes underlying your experiment. That's often where interpretation begins.

A volcano plot might identify hundreds of significant proteins. But researchers rarely care about a list of proteins. They want to understand: • Which pathways are changing? • Which biological processes are enriched? • What mechanisms may be driving the phenotype?

A list of proteins isn't the answer. Biology is. Differential expression tells you what's changing. GO enrichment helps explain what those changes mean. In this example, inflammatory and cytokine signaling emerge as some of the most enriched biological processes. 👇

I’ve been re-analyzing a public proteomics dataset and noticed that cancer profiles can look more similar to other cancers than to normal tissue profiles. Is that expected biology, or an artifact of analysis choices?

Large-scale proteomics analysis shouldn't take weeks. Working with frankligy.bsky.social and Mark Yarmarkovich, Tesorai processed 2,500 immunopeptidomics files in under 5 hours—a workflow that previously required more than 4 weeks. Publication: www.biorxiv.org/content/10.1...

Proteomics datasets have grown dramatically in size and complexity. Analysis infrastructure needs to evolve alongside the data.

Honored to see our work highlighted by Dr. Yu-Ju Chen (Academia Sinica) in her #HUPO2025 plenary talk yesterday. We’re thrilled to support her and her team's groundbreaking research in proteomics and lung cancer.

Incredible energy at #HUPO2025! Huge thanks to everyone who has been stopping by the Tesorai booth to see our live demos in action! We’re thrilled by the excitement, thoughtful conversations, and momentum around what we’re building. Grateful to be part of such a passionate proteomics community!

We’re excited to share that Tesorai will be hosting a booth at the HUPO 2025 World Congress in Toronto! Find us at Innovation Row – Table TP3! Stop by for live demos of our AI-powered platform and try out Tesorai Chat in action.

Intro to Tesorai (Search + Chat) If you're working with proteomics data and tired of writing custom code or clicking through clunky tools, we built something that can help. Tesorai lets you process raw mass spec files quickly. And explore your results just by asking questions in chat. Links below:

We are in Barcelona! Excited to sponsor the 2025 Gordon Research Conference on Decoding Microproteins! Dejan will be presenting our poster - “Tesorai Search: Large pretrained model boosts identifications without the need for Percolator.” Come find us and say hi!

Why We Built This: We started building Tesorai because we kept running into the same problem: mass spec analysis is still too challenging and tools can be difficult to use. We wanted something fast, reliable, and flexible enough to work with the questions scientists actually have.

We're a small group of former Google/Verily engineers who’ve spent years building large-scale AI systems. Now we’re working on something different: building advanced AI to help scientists make more sense of raw mass spec proteomics data.

#teammassspec does anyone have more info on what's behind the restrictions to sell mass spectrometers to China? www.bis.gov/press-releas...

And you can learn more about our approach here: www.biorxiv.org/content/10.1...

Interesting to see how improving identification accuracy in #massspectrometry #proteomics also improves the quantification precision. On the public LFQBench benchmark, Tesorai Search without MBR outperforms tools like MaxQuant, FragPipe, and AlphaPept even when they have MBR enabled!