Vadim Demichev

We are delighted to release 𝐃𝐈𝐀-𝐍𝐍 𝟐.𝟑.𝟏, with a groundbreaking 𝐈𝐧𝐟𝐢𝐧𝐃𝐈𝐀 module for fast searches against huge databases and support for 𝐃𝐃𝐀 data. Release notes: github.com/vdemichev/DiaN…

@TenzerLab Long awaited work! Huge congrats!

Our benchmarks reveal inflated true FDR (3–5%) when modified peptidoforms are considered and highlight peak-matching errors in match-between-runs analyses. Great collaboration with the labs of Andreas Hildebrandt and Mathias Wilhelm. (2/2) Preprint: researchsquare.com/article/rs-903…

What an amazing work! Regular entrapment FDR validation can be circumvented in a number of ways. But here comes simulated data with known ground truth. Great to see DIA-NN 2.0 excel at sensitivity while controlling FDR and false localisation rates.

@TenzerLab Link?

New preprint out! Timsim: a framework to simulate native #timsTOF dda-PASEF and dia-PASEF datasets with full ground-truth annotation, enabling precise benchmarking of #FDR and phosphosite localization errors in #proteomics and #immunopeptidomics workflows. (1/2)

Now in @CellCellPress: We profiled cerebrospinal fluid proteomes from 5,000 neurology patients by mass spectrometry — mapping protein changes across stroke, brain cancer, infections & autoimmune diseases, revealing shared and disease-specific signatures. sciencedirect.com/science/articl…

Paper: pubs.acs.org/doi/10.1021/ac…

Solving the computational challenge of phosphoproteomics with 𝐏𝐡𝐨-𝐓𝐢𝐩: One-Pot Dephosphorylation for Rapid and Sensitive Analysis of DIA Phosphoproteomics Data. Now out in Analytical Chemistry! Makes predicted phosphopeptide libraries 10x-20x smaller. Link below.

Ever wondered how the human liver looks like at single-cell, spatial protein resolution? We used single-cell Deep Visual Proteomics to map human liver zonation at the protein level - one hepatocyte at a time. Our paper is out in @NatMetabolism! nature.com/articles/s4225…

Discovery proteomics → clinical diagnostics? ADAPT-MS makes it possible by adapting to each sample's protein coverage on-the-fly. No imputation, no fixed panels, multiple diagnostic questions from one measurement. Out now in @NatureComms. nature.com/articles/s4146…

📢 Publication alert🌶️! Developed in #MacCossLab, #Mag_Net offers a cost-effective method for deep plasma profiling. We are happy to see this workflow gathering momentum for studying #NeurodegenerativeDiseases biorxiv.org/content/10.648… sciencedirect.com/science/articl…

@OdedRechavi @X @grok Indeed. I have switched to LinkedIn almost exclusively for getting news about papers. X is full of 'funny stuff' and 'political stuff', I tried to shift the focus of what I see to AI and coding by selecting the relevant topics, but still get bombarded by irrelevant things.

Two options: 1. The @X algorithm is just broken 2. The algorithm intentionally ignores scientists (news, tech & entertainment less effected) It’s probably #1. We heard that they were going to fix it (@grok), but this didn’t happen. Exposure to science is down >90%.

Researchers at @sanquin show how MS-based plasma proteomics can scale to large clinical cohorts using diaPASEF on an Evosep + @bruker timsTOF HT - delivering robust, high-throughput, reproducible analysis at scale. Read more: pubs.acs.org/doi/full/10.10…

@animesh1977 Hah, not yet :)

@DemichevLab Awesome! Now that DDA-NN support is there, did you also run the same samples in DDA mode?

We acquired a large-scale mixed-species benchmark, with variable background, to comprehensively assess quantitative accuracy of proteomics. Key features: - 192 runs, 0.75ng - 15ng of variable human cell line backgroud. - Can dissect the impact of both random and systematic errors. - Can test how quantitation algorithms scale with experiment size and sample heterogeneity. Our insights based on the data: biorxiv.org/content/10.648…. PRIDE repo will be made public in the next days.

@slavovLab @MZG_Lab Oh wow, congrats!

Our latest article is out in Cell ! Together with the @MZG_Lab, we show that fertilization triggers proteomic asymmetry in mammalian zygotes, giving rise to alpha vs. beta 2-cell blastomeres with distinct developmental potential. cell.com/cell/fulltext/…

Solving the computational challenge of phosphoproteomics with 𝐏𝐡𝐨-𝐓𝐢𝐩: dephosphorylation on-tip identifies the sequences of phosphorylated peptides. This serves as a basis for predicted spectral libraries, reducing the search space 10x-20x. biorxiv.org/content/10.110…

Latest by Claudia Langenberg and her team provides insights into protein loss-of-function (LOF) mutations using three proteomics technologies within the Genes and Health cohort. This analysis focuses on the impact of complete LOF mutations on protein plasma abundance. The study involves 199 individuals who exhibit complete predicted LOF for a protein due to being homozygous for a rare LOF allele. Proteomics measurements from Seer, Olink, and Somalogic reveal significant changes of protein expression levels in blood in these individuals. The results indicate that the respective proteins are often severely underexpressed, with some instances of overexpression. Notably, the Seer measurements demonstrate a complete absence of the protein in a number of LOF individuals, as illustrated in Figure 2. The results are further analyzed for their connection to rare diseases. A first-in-kind study and an interesting comparison of three leading cohort proteomics technologies. @DemichevLab @slavov_n @ksuhre @manoliskellis @DeryaTR_