Sign in

Bo Wen

@bo-wen.bsky.social
151 followers 391 following 3 posts
PostsRepliesMedia
Reposted by Bo Wen
Thilo Muth @drmuth.bsky.social · 17/07/2026
Very nice Java GUI. Nice (inofficial) successor of our previous DeNovoGUI software. Also supports mapping of peptides to reference databases - cool! 😎
031
Reposted by Bo Wen
Michael MacCoss @maccoss.bsky.social · 03/06/2026
Back to the Future! New preprint. A while back, we recognized that resonance excitation CID had real advantages over beam-type CID for data independent acquisition. The catch was speed: reCID was simply too slow to be practical. Not anymore. #proteomics #ASMS #DIA
2186
Reposted by Bo Wen
Lindsay K Pino @lindsaykpino.com · 31/03/2026
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.
2166
Reposted by Bo Wen
UW Genome Sciences @uwgenome.bsky.social · 12/11/2025
Congratulations to Mike MacCoss on receiving the Donald F. Hunt Distinguished Contribution in Proteomics Award from US HUPO! us-hupo.org/Distinguishe...
us-hupo.org
US HUPO - Distinguished Contribution Award
02711
Reposted by Bo Wen
UW Genome Sciences @uwgenome.bsky.social · 12/11/2025
Congratulations to Bill Noble on receiving the 2026 Gil Omenn Computational Proteomics Award from US HUPO! us-hupo.org/Computationa...
us-hupo.org
US HUPO - Computational Proteomics Award
0158
Reposted by Bo Wen
Michael MacCoss @maccoss.bsky.social · 06/11/2025
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...
nature.com
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...
03810
Reposted by Bo Wen
Nature Methods @natmethods.nature.com · 28/08/2025
DeepMVP is a deep learning framework to predict PTM sites and variant-induced alterations across 6 common PTMs. www.nature.com/articles/s41...
nature.com
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...
0153
Reposted by Bo Wen
Nature Methods @natmethods.nature.com · 07/07/2025
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...
0134
Reposted by Bo Wen
Vadim Demichev @vadim-demichev.bsky.social · 02/07/2025
(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.
2161
Reposted by Bo Wen
wnoble.bsky.social @wnoble.bsky.social · 16/06/2025
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...
nature.com
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...
13110
Reposted by Bo Wen
Michael MacCoss @maccoss.bsky.social · 16/06/2025
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.
2439
Reposted by Bo Wen
Nature Methods @natmethods.nature.com · 16/06/2025
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...
nature.com
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...
0114