@saezlab
Account of the Saez-Rodriguez lab at EMBL-EBI and Heidelberg University. We integrate #omics data with mechanistic molecular knowledge into #opensource #ML methods Website: https://saezlab.org/ GitHub: https://github.com/saezlab/
Led by @martingarridorc.bsky.social and Clement Potel with the help of @miraburtscher.bsky.social, Isabelle Becher, @pablormier.bsky.social, @smuellerdott.bsky.social. Supervised by Mikhail Savitski and @juliosaezrod.bsky.social. With support from @aihcluster.bsky.social and @embl.org facilities.
Original preprint: doi.org/10.1101/2024... Want more details on the data, prior knowledge, methods, and ground-truth sets?
Everything is in the paper and the accompanying Zenodo resource: zenodo.org/records/1839...
Why does this matter? This work challenges the traditional, largely linear view of signaling pathways and proposes a more complex, systematic, and data-driven framework for studying signaling at scale.
The result? While some combinations (e.g. literature and diffusion methods) recovered ~20% of known interactions, over 90% of interactions were missing from ground-truth sets, pointing to many potentially novel connections.
Using these data, kinase–substrate interactions, and network inference methods, we tested how well different resources recover known (ground-truth) signaling interactions between kinases.
We combined published phosphoproteomics data with three newly generated datasets to create the most comprehensive resource to date on the EGF signaling response, comprising more than 45,000 high-confidence phosphosite identifications
In this manuscript, we adopt the perspective of a naive researcher with the goal of learning the EGF signaling pathway — specifically kinase–kinase interactions — using phosphoproteomics and prior knowledge
Most of these pathways were built from small-scale, perturbation-based biochemical experiments. But how well can we recover known signaling pathways using a systematic, data-driven approach without perturbations?
What is a signaling pathway? For decades, researchers have used conceptual pathway maps to explain how cells transmit information. These maps have also been used to interpret molecular data and guide drug development efforts.
Interested in kinase-driven signaling interactions? Check out our (now peer-reviewed) paper together with @savitski-lab.bsky.social on reconstructing signaling networks from phosphoproteomics data and prior knowledge:
➡️ doi.org/10.1038/s414...
This month we welcomed Francisca Gaspar Vieira, PhD student from @brittavelten.bsky.social's lab, to visit us at @ebi.embl.org for 6 months 🎉
She will continue to develop probabilistic factor models explicitly incorporating uncertainty in the estimation of perturbation effects in single-cell data
next week 🔜
Happy to share new work led by @miraburtscher.bsky.social, together with colleagues from @savitski-lab.bsky.social, @saezlab.bsky.social (shout-out to @martingarridorc.bsky.social), @zimmermannlab.bsky.social and others.
Original post + paper below! 👇
On March 4th, our @ricoramirez.bsky.social will share how we can currently study tissue remodelling with spatial transcriptomics data at a webinar from @training.ebi.embl.org.
This webinar series includes a great lineup of speakers. For free registration see link below ⬇️
New preprint from my team! led by @remitrimbour.bsky.social in collaboration with the @saezlab.bsky.social, we developped ReCoN a new method to model multicellular coordination and its underlying molecular mechanisms.
📜 Paper: lnkd.in/eJ8SfFNH
💻 Code: lnkd.in/e-qx2iNp
This month we welcome 2 new members and 1 visitor to our lab! 🎉 Veronika Kedlian as a postdoc, Hugo Hakem as a PhD student, and @francescadrummer.bsky.social as a visiting PhD student 🎉
Congrats! We’re happy to have contributed to the Atlas of Human Inflammation, improving the interpretability of inflammatory signatures through inference of transcription factor activity (Jose Liñares Blanco, @ricoramirez.bsky.social and @juliosaezrod.bsky.social)
www.linkedin.com/posts/holger...
We recently posted a "2025 Publication Countdown" series on LinkedIn. See here ➡️ www.linkedin.com/company/saez...
We acknowledge the funding from the Heidelberg Faculty of Medicine at @uniheidelberg.bsky.social through the Medical Data Scientist Fellowship.
This study was led by @ahmetrifaioglu.bsky.social, with supervision by @juliosaezrod.bsky.social and @tanevski.bsky.social, and with contributions from @asarigun.bsky.social and @denizgermen.bsky.social. In collaboration with the @bb-lab.bsky.social, with contributions from Egle Helene Ervin.
📌 Across multiple breast cancer proteomic datasets, SpaCEy robustly stratifies patients by overall survival, both across and within established clinical subtypes.
📌 In a spatial proteomic lung cancer cohort, SpaCEy identifies distinct spatial arrangements and protein programs associated with disease progression.
📌 The model highlights compact spatial patterns involving a small set of key protein markers underlying patient stratification, supporting interpretability and clinical relevance.
See 👇 our new manuscript introducing SpaCEy, an explainable method for predicting clinical outcomes from spatial omics data 🧬
📄 Paper: www.biorxiv.org/content/10.6...
💻 Code repo: github.com/saezlab/SpaCEy
🤗 We welcome Jay Chow (Chi Lung), our new Scientific Database Curator. Jay will be joining a collaborative effort between SaezLab, @ebi.embl.org FG team, and GSK for the curation of fibrosis datasets and integration into the Expression Atlases and ArrayExpress collection in BioStudies.
📍 Latest OmniPath paper is out now! ➡️ academic.oup.com/nar/advance-...
It was an honor to speak about Systems Biology of Kidney Disease at the American Society of Nephrology meeting www.youtube.com/watch?v=YLVs...
reflecting from my perspective as patient-scientist (www.nature.com/articles/s41...) & sharing work of @saezlab.bsky.social sp. within www.iganatlas.org
📄 BioContextAI is now slightly updated and published @natbiotech.nature.com
➡️ www.nature.com/articles/s41...
We thank all data authors (incl. Kory Lavine, Patrick Ellinor, and Norbert Hubner’s labs, among others) and enrolled patients. We acknowledge funding from DFG through CRC1550. All code available at github.com/saezlab/rehe...
This study was co-led by @ricoramirez.bsky.social and @jlanzer.bsky.social with supervision by @juliosaezrod.bsky.social and help by Jose Linares, and the group of Norbert Frey (Marco Steier and Ashraf Rangrez) who performed the experimental work.