A new preprint introduces π-MSNet: a billion-scale, MS data portal with 1.66B spectra, built for machine/deep learning, benchmarking, and reproducibility.

URL:
www.biorxiv.org/content/10.6...

Open, living, and community-driven-this is a big step toward accelerating innovation in proteomics 🚀

Next-generation proteomics in medical laboratories: metrologically sound quantitative protein tests vs. innovative and personalized proteome patterns In precision medicine protein phenotypes are foreseen that combined with pattern recognition tools exhibit great potential in guaranteeing safe and accurate test results for patient management and int...

van der Burgt and Cobbaert, "Next-generation proteomics in medical laboratories: metrologically sound quantitative protein tests vs. innovative and personalized proteome patterns" doi.org/10.1515/cclm...

Why clinical proteomics faces a mass spectrometry vs. high-throughput profiling dilemma This Clinical Chemistry and Laboratory Medicine review examines a central challenge in precision medicine: whether medical laboratories should prioritize metrologically sound, proteoform-resolving pro...

Clinical proteomics is at a crossroads: Should labs prioritize the precision of mass spectrometry or embrace the speed of high-throughput profiling? ⚖️🤔 www.news-medical.net/news/2026041... #Proteomics #PrecisionMedicine @degruyterbrill.bsky.social

Impressive!

The Synthetic Epitope Atlas: High-Throughput Design and Validation of De Novo Antibody-Antigen Complexes
Altieri et al.
bioRxiv 2026.04.17.719295; doi: doi.org/10.64898/202...

Flyer for NIST26 full GC/MA chromatogram analysis by NIST EI Library

#TeamMassSpec NIST26 is set to be the biggest change since NIST98 - a revolutionary rather evolutionary upgrade for both GC-MS and LC-MS
enquiries@spectrometrics.com

Editorial for the Special Honor Issue Honoring Dr. Carlito B. Lebrilla Mass Spectrometry Reviews, EarlyView.

(MS Reviews) Editorial for the Special Honor Issue Honoring Dr. Carlito B. Lebrilla: Mass Spectrometry Reviews, EarlyView. #MassSpectromRev #MassSpecRSS

NovoGlyco: mapping protein glycosylation in prokaryotes
Martin Pabst, Dinko Soic
bioRxiv 2026.04.15.718822; doi: doi.org/10.64898/202...

Deep visual proteomics uncovers nociceptor diversity and pain targets - Nature Communications Sensory neuron subtypes are defined by transcriptomics, but their proteomic identities remain unclear. Here, authors show distinct protein signatures of electrophysiologically defined nociceptors and ...

Excited to share our new @natcomms.nature.com study with the @garyrlewin.bsky.social lab and @amapruns.bsky.social. Using deep visual proteomics, we created the first neuronal subset-resolved proteomic map of sensory neurons with potential implications for pain treatment.
go.nature.com/481nr4R

MetaDIA: A DDA-free Database Reduction Strategy for DIA Human Gut Metaproteomics Abstract. Microbiomes, especially within the gut, are complex and may comprise hundreds of species. The identification of peptides in metaproteomics presen

MetaDIA: A DDA-free Database Reduction Strategy for DIA Human Gut Metaproteomics url: academic.oup.com/gpb/article/...

Come join us a #bioinformatics / #computationalbiology postdoc to explore the #microbiome using #metaproteomics and #metagenomics

Microbiome Bioinformatician (Postdoc) - Metagenomics and Metaproteomics @RalserLab
Charité Universitätsmedizin Berlin

See the full job description on jobRxiv: https://j

Metabolomics across scales: from single cells to population studies - Nature This Perspective reviews the potential and the challenges of metabolomics approaches, encompassing both single-cell and population-scale metabolomics.

Metabolomics across scales: from single cells to population studies

Gene regulatory landscape dissected by single-cell four-omics sequencing - Nature Combining single-cell parallel profiling of genome conformation, histone modifications, chromatin accessibility and gene expression reveals dynamics and intranuclear spatial clustering of epigenome pr...

A study published in Nature presents CHARM, a single-cell 'four-omics' sequencing method that profiles genome conformation, histone modifications, chromatin accessibility, and gene expression within the same cell.🧪👇
www.nature.com/articles/s41...

Review on 20 years of Orbitrap MS!
analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/...

From early days to today’s hybrid & Tribrid systems, it highlights how innovation, accessibility, and new applications shaped the field.
Orbitrap => true workhorse of modern MS 🔬

Ubuntu Proteomics Summer School 2026, George South Africa! YouTube video by Ubuntu Proteomics Summer School

The #UPSS2026 video has landed! Thank you to all the participants, organizers, sponsors, facilitators and collborators for making this event such a success! Please follow our socials to hear about the launch of #UPSS2027... #LearnConnectGrowExplore with #TeamMassSpec
youtu.be/5BvnY-RyqRo

InstaNovo-P: A de novo peptide sequencing model for phosphoproteomics

Preprint:
doi.org/10.1101/2025...

🚨 The final programme for the Annual Proteomics Gathering at the Faculty of Pharmacy, Universidad Complutense de Madrid on April 16th is officially ready! 🎉

#AnnualProteomicsGathering #Networking #ScienceCommunity #YoungResearchers #InnovationInScience #FlashTalks #EarlyCareerResearchers #YPIC

I thought it was quite mind boggling to see that around 10% of the protein in a standard yeast based bread is actually yeast protein! Here our #metaproteomics analysis of microbial protein in fermented foods
pubs.rsc.org/en/Content/A...
Congratulations to first authors Laura Winkler and Ayesha Awan

Improvements to Casanovo, a Deep Learning De Novo Peptide Sequencer Casanovo is a state-of-the-art deep learning model for de novo peptide sequencing from mass spectrometry and proteomics data. Here, we report on a series of enhancements to Casanovo, aimed at improvin...

Big fan of this lab’s work!
Casanovo is already state-of-the-art for de novo sequencing; and these improvements take it even further: better score interpretability, database search integration, faster runtimes, and user-friendly workflows.
pubs.acs.org/doi/10.1021/...

New Preprint: NovoTax identifies the closest prokaryotic genome directly from raw bottom-up proteomics data. The approach combines peptide de novo sequencing tools on DIA data with an optimized implementation of peptide searching through an extensive genome database.
www.biorxiv.org/content/10.6...

We evaluated quantification methods for #metaproteomics and found that area under the curve quantification (AUC) outperforms spectral counting. Importantly, using match between runs for AUC quantification results in lots of false detections and should not be used www.biorxiv.org/content/10.6...

ECLIPSE: Exploring the dark proteome of ESKAPE pathogens through the sequence similarity network of the Protein Universe Atlas www.biorxiv.org/cont...

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#proteomics #prot-preprint

In-source fragmentation in mass spectrometry-based proteomics: prevalence, impact, and strategies for mitigation
doi.org/10.64898/202...

Sure. AI catalyzes presumably fast and easy solutions there as well. Still, we have a choice. 😉

I agree. However, one pragmatic way to tackle this is more to evaluate if students have understood the basic concepts of a subject by getting into live situations (explain a math formula in front of the class) and discussions (on a paper read). I am fine with students using LLMs for learning btw…

"The department needs papers, because papers justify funding, & funding justifies the department. ... Whether that student walks out the door five years later as an independent thinker or a competent prompt engineer is, institutionally speaking, irrelevant."
ergosphere.blog/posts/the-ma...

This is exactly the fear that I have when seeing the latest gen of students. I actually believe that AI will make us dumber instead of boosting academic or economic progress…

In all analyses across different data sets and algorithms, I did so far: longer peptides are still very hard to resolve via de novo… It feels like this exactly where more tailored protocols could make a difference (besides fancy ML/AI Methods nowadays), but I am a hopeless dry-lab guy…

It seems plausible that spectra generated under such conditions might be more informative for sequence reconstruction, especially for peptides that are currently hard to capture.
Curious how much room there is on the acquisition side to systematically improve de novo performance?

And maybe extending that beyond existing datasets to future ones: I wonder whether more tailored protocols could make a difference.
For example, tuning parameters like collision energy specifically with de novo interpretation in mind.

The raw data is there, but
I was thinking more about effects introduced during MS acquisition with instrumental parameters (impact on de novo > db search). Spectral noise and incomplete ion ladders have a strong impact on de novo.
But I agree that such public data should be considered ofc.