It has been added to the mzTab output: casanovo.readthedocs.io/en/latest/fi...

Getting the ol' grad school gang back together with Carafe2 -- Bo Wen (@maccoss.bsky.social and Bill Noble) and @jspaezp.bsky.social (@willfondrie.com at @talusbio.bsky.social) teamed up for essentially some late night hackathons to build out Carafe for @brukercorporation.bsky.social timsTOF data.

US HUPO - Distinguished Contribution Award

Congratulations to Mike MacCoss on receiving the Donald F. Hunt Distinguished Contribution in Proteomics Award from US HUPO!
us-hupo.org/Distinguishe...

US HUPO - Computational Proteomics Award

Congratulations to Bill Noble on receiving the 2026 Gil Omenn Computational Proteomics Award from US HUPO!
us-hupo.org/Computationa...

Carafe enables high quality in silico spectral library generation for data-independent acquisition proteomics - Nature Communications Accurate spectral libraries are essential for analyzing data-independent acquisition (DIA) proteomics data. Here, the authors present Carafe, which trains on DIA data to build experiment-specific spec...

Fantastic project led by @bo-wen.bsky.social. Excited to see the future uses of AI and transfer learning in proteomics. #massspec #proteomics
www.nature.com/articles/s41...

DeepMVP: deep learning models trained on high-quality data accurately predict PTM sites and variant-induced alterations - Nature Methods DeepMVP is a deep learning framework for predicting PTM sites and variant-induced alterations across six modification types, including phosphorylation, acetylation, methylation, sumoylation, ubiquitin...

DeepMVP is a deep learning framework to predict PTM sites and variant-induced alterations across 6 common PTMs.

www.nature.com/articles/s41...

The FDR control in the newer versions looks much better. DIA-NN is an excellent tool. We use it a lot in our lab.

Cascadia from @wnoble.bsky.social is a mass spec-based de novo sequencing model that uses a transformer architecture to handle data-independent acquisition data and achieves substantially improved performance across a range of instruments and experimental protocols. www.nature.com/articles/s41...

The FDR control in the newer version of DIA-NN is much improved on the datasets I have looked at.

(1/2) We have always validated FDR internally on several datasets. Bo Wen and colleagues discovered that FDR of DIA-NN 1.8.1 was anti-conservative on some (but not other) datasets - for some unknown reason. So we fixed it in 2.0 :) Now q-values are more accurate and fluctate less across datasets.

Assessment of false discovery rate control in tandem mass spectrometry analysis using entrapment - Nature Methods A theoretical foundation for entrapment methods is presented, along with a method that enables more accurate evaluation of false discovery rate (FDR) control in proteomics mass spectrometry analysis p...

Error control in proteomics mass spectrometry analysis is hard. We came up with a way to evaluate error control. Upshot: for old-school DDA data, not so bad. For DIA data, no existing tool successfully controls the false discovery rate!

www.nature.com/articles/s41...

Excited to see this published! It is a good step in the process for people to assess their FDR control in proteomics experiments. Great work from @bo-wen.bsky.social and @urikeich.bsky.social in particular who drove this.

Assessment of false discovery rate control in tandem mass spectrometry analysis using entrapment - Nature Methods A theoretical foundation for entrapment methods is presented, along with a method that enables more accurate evaluation of false discovery rate (FDR) control in proteomics mass spectrometry analysis p...

Assessing error control is fundamental in mass spectrometry-based proteomics. @bo-wen.bsky.social @maccoss.bsky.social @urikeich.bsky.social et al introduce a theoretical foundation for entrapment along with a method for more accurate evaluation of FDR control.
www.nature.com/articles/s41...