Interpretable machine learning leverages proteomics to improve cardiovascular disease risk prediction and biomarker identification
->Nature | #MachineLearning #Disease #Health | More info from EcoSearch
Our paper is out in Nature today! We use Deep Visual Proteomics (DVP) to dissect Ξ±1-antitrypsin deficiency (AATD) in human liver at single-cell resolution.
Let us take a tour through proteotoxic stress in intact human tissue β one hepatocyte at a time.
www.nature.com/articles/s41...
Preprint alert βΌοΈ
Excited to share our work investigating liver zonation in human health and disease with our advanced single-cell Deep Visual Peoteomics framework!
π¨NEW PUBLICATION ALERTπ¨: In a paper out now in
@science.org we describe a way to build synthetic phosphorylation circuits with customizable sense-and-response functions in human cells. Check it out at science.org/doi/10.1126/....
It's time for individuals and organizations in Europe and other democratic countries to move mission- or life-critical IT services and infrastructure outside the reach of the US government; noting that US tech companies have already largely subordinated themselves.
www.huber.embl.de/group/posts/...
What an outstanding study! This majorly expands our understanding by showing that glycosylated RBPs are not only present but also organized into specialized clusters. New avenues for cellular communication and therapeutic delivery strategies! Many congratulations @raflynn5.bsky.social and team.
Mindblowing new study by @raflynn5.bsky.social @bostonchildrens.bsky.social, cell surface RNA-binding proteins form nanoclusters with #glycoRNA and mediate cell-penetrating peptide entry into cells π
www.cell.com/cell/abstrac...
Out today in Nature Genetics: Using MS-based proteomics, we mapped 1,200+ plasma proteins in 2,100+ children, showing how genetics & development shape blood protein levels during childhood.
nature.com/articles/s41588-025-02089-2
#PediatricProteomics #pQTL
First author @liliniu.bsky.social explains β¬οΈ
You are absolutely on the spot, always with minimum thickness of the fcap. As per the Oxford study. All the plaques we used have histologies available. Unfortunately we didn't have the time resources to profiles all the plaque tissues at MUC biobank. I'll email you tonight :)
Thank you Luke! @erwinschoof.bsky.social talked highly about you. If possible, may we have a zoom call? It would be good to build some synergies/exhabges between our projects, and get an independent, unbiased perspective on it! :)
I appreciate the detailed reply. I agree & experimentally observed that convergence to the 1st moment (i.e. mean) leads to underestimating 2nd+ moments. Also, MICE was a little better at preserving the higher moments. I used the matrix norm of the covariance matrix to measure the imputation artefact
My favorite books, 2024
This is a very informative article. Reducing 37 imputation methods into 5 major groups helps grasp their diversity. May I ask how Neighbor/Regression and NN-based approaches deal with heteroskedasticity in quantitative data (ex. MS-proteomics)? How would it compare in MICE approaches? Thank you!
Our draft of proteomes of clinically advanced, #atherosclerosis carotid plaques. We used #proteomics to distinguish between stable and vulnerable plaques. Thanks to the members of @mannlab.bsky.social and Maegdefessel (TUM clinic) labs, as well as the #Cardiology & Surgery departments (TUM clinic).
π Robust and high sensitivity #proteomics: Our Nature protocol demystifies #PASEF workflows and provides ready-to-use dia-PASEF & synchro-PASEF methods. Find out how to achieve 7,000 protein groups or 29,000 phosphosites in 21min. Let's explore! #TeamMassSpec #Bruker doi.org/10.1038/s415... 1/π§΅
My general approach to biostats is that the stats problems we just discovered were solved by WH 10 years ago :)
www.nature.com/articles/nme...
Yes, and entirely common. Wolfgang Huber's Independent hypothesis weighting approach is great for adjusting p-vals, and accommodates heteroscedasticity present in proteomics data. Briefly, you adjust p-vals based on bins defined by some covariates (ex. protein median).
The fox is in the henhouse.
Our mipDVP workflow integrates 22-marker imaging with Deep Visual Proteomics to spatially map cell-type proteomes in hot/cold tumors, revealing distinct immune landscapes, macrophage barriers, T cell adaptations to hypoxia & tumor heterogeneity. Online in Molecular Cell.
doi.org/10.1016/j.mo...
Looking for rapid, deep & reproducible proteomics? Follow our @Nature protocol to get 7k proteins & 29k phosphosites in just 21 min! Complete #PASEF workflow using optimal dia-PASEF, synchro-PASEF & py_diAID. From method development to analysis. #TeamMassSpec @patiskowronek.bsky.social explains π
Our Deep Visual Proteomics workflow maps protein networks in bladder, prostate, seminal vesicle & lymph node Signet Ring Cell Carcinoma, revealing DNA damage response alterations & immune signatures that could guide therapy choice. Out now in NPJ Precision Oncology! rdcu.be/d8KyK
Mike's Sage is outstanding. When I first used it, I thought it had errored out. Turns out it was done.
A universal spectrum annotator for complex peptidoforms in mass spectrometry-based proteomics www.biorxiv.org/cont...
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#proteomics #prot-preprint
I would frame it another way. Science is a method to answer questions. We have drifted away from asking questions, or at least from asking good, focused questions, framing testable hypotheses and then testing with good experiments. Big datasets can be very useful, but we need good questions.
For a good positive start, just a reminder that Claire Patterson was one of the greatest mass spectrometrist. It is very possible that most of us are alive because of him, and his will and determination to fight uphill. #proteomics #teamMassSpec
