iiinova — where your digital self keeps evolving

Saez-Rodriguez Group @saezlab.bsky.social · 01/10/2026

This month we welcomed two new PhD students and a new postdoc to the lab, Stanislaus Stein, Amber Fijn and Alicja Wojciechowska. 🎉

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Saez-Rodriguez Group @saezlab.bsky.social · 29/09/2026

Happy to see the peer-reviewed version of SpaCEy now out: 📄 Published paper: www.nature.com/articles/s41... 💻 Code: github.com/saezlab/SpaCEy

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Saez-Rodriguez Group @saezlab.bsky.social · 28/09/2026

Introducing mc-ASTRA, an open-source Python framework for studying how tissues vary and remodel across patients, perturbations, time points and other biological contexts. Manuscript: www.biorxiv.org/content/10.6... Package: saezlab.github.io/mc-astra/

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Saez-Rodriguez Group @saezlab.bsky.social · 07/09/2026

🧵 Introducing Karenina, an open-source framework to evaluate LLMs & agents: doi.org/10.64898/202...

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Saez-Rodriguez Group @saezlab.bsky.social · 20/08/2026

Our tool MetaProViz is now out in Molecular Systems Biology: doi.org/10.1038/s443... Since our preprint we: - advanced our feature processing workflow - added metabolite-sets to MetSigDB - added metabolite-set visualization to aid functional analysis

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Saez-Rodriguez Group @saezlab.bsky.social · 04/08/2026

Check out our recent review ➡️ "Towards Principled Evaluation of Single-Cell Perturbation Prediction Models" More on LinkedIn post: lnkd.in/p/dKuF6f7A

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Saez-Rodriguez Group @saezlab.bsky.social · 09/07/2026

🧵 ParTIpy, our Python package for Pareto Task Inference just got published in Molecular Systems Biology (Peer reviewed at Review Commons) 🔗 Manuscript: link.springer.com/article/10.1... 💻 Code: github.com/saezlab/part... 📚 Docs: partipy.readthedocs.io/en/latest/

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Saez-Rodriguez Group @saezlab.bsky.social · 25/06/2026

Scaling to TCGA-KIRC kidney cancer (526 patients), topology-based subgroups associate with annotated immune subtypes. In silico, knockouts nudge simulated APAF1/CASP9/BIRC5 activity toward patterns seen in cytotoxic-infiltrate tumours. 🔬

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Saez-Rodriguez Group @saezlab.bsky.social · 25/06/2026

In the SU2C-MARK lung cancer cohort, subgroup models reproduce patient-specific up/down dynamics. Per-protein error analysis flags regions to refine, and in silico knockouts (e.g. LTBR, CD40 acting on TRAF2) nominate candidate targets to shift non-responders toward responder profiles.

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Saez-Rodriguez Group @saezlab.bsky.social · 25/06/2026

On TCGA prostate cancer, our automated networks recover much of a manually curated PKN, while also reflecting subgroup-specific variation that a single curated network wouldn't. We fit both Boolean (fast) & logic-ODE (continuous, richer dynamics) models via CellNOpt (github.com/saezlab/Cell...).

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Saez-Rodriguez Group @saezlab.bsky.social · 25/06/2026

FICUS uses COSMOS ( doi.org/10.15252/msb...) to infer patient-specific signalling networks top-down from omics, no manual PKN curation. It then treats inter-patient variability as the 'perturbations', clustering patients by network topology into subgroups that share recurrent network structure. 🧬

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Saez-Rodriguez Group @saezlab.bsky.social · 25/06/2026

🧵 New preprint: Logic models can simulate cancer signalling & screen drug targets in silico, but they need perturbation data & hand-curated networks patients lack. We present FICUS for building dynamic logic models directly from patient omics. 📄 doi.org/10.64898/202...

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Saez-Rodriguez Group @saezlab.bsky.social · 22/05/2026

Our alumna Sophia Müller-Dott was honored with the MTZ Award for Systems Medicine for her PhD work. Congratulations, Sophia! 🎉 A special thanks to Monika and Thomas Zimmermann from the MTZ Foundation for their enduring support of Systems Medicine. 🙌

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Saez-Rodriguez Group @saezlab.bsky.social · 13/05/2026

Using a new spatial transcriptomic cohort of lupus nephritis kidney biopsies, generated in collaboration with Michael T. Eadon’s team, we found that blood-derived programs were enriched in immune-infiltrated glomerular regions in lupus patients but not in healthy samples.

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Saez-Rodriguez Group @saezlab.bsky.social · 13/05/2026

When mapped onto an external longitudinal blood transcriptomic cohort, these programs predicted future flare risk and highlighted candidate blood protein biomarkers detectable by proteomics.

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Saez-Rodriguez Group @saezlab.bsky.social · 13/05/2026

These programs revealed a rewiring of immune coordination during disease activation, including changes in cell-to-cell interactions and in how transcriptional “tasks” are allocated across immune cell types.

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Saez-Rodriguez Group @saezlab.bsky.social · 13/05/2026

First, using two independent single-cell PBMC cohorts, we inferred patient-level transcriptomic immune programs that capture both SLE-vs-health differences and heterogeneity within SLE.

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Saez-Rodriguez Group @saezlab.bsky.social · 13/05/2026

1/🧵 New preprint! We built a patient-level map of systemic lupus erythematosus using single-cell blood transcriptomics, linking multicellular immune coordination to patient heterogeneity, future disease activity, and potential tissue pathology. ➡ doi.org/10.64898/202...

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Saez-Rodriguez Group @saezlab.bsky.social · 29/04/2026

This month we welcome Ajita Shree as a postdoctoral researcher, who will be working on computational methods for cell–cell communication 🎉. Ajita has a background in developing deep generative models for single-cell & spatial transcriptomics.

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Saez-Rodriguez Group @saezlab.bsky.social · 17/03/2026

🩸🥃 We showed that urine and plasma proteomics reflects underlying injury, and plasma proteins were predictive of future CKD and AKI in an external cohort. Thinking of kidney disease as a continuum of damage rather than discrete categories could guide future biomarker discoveries.

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Saez-Rodriguez Group @saezlab.bsky.social · 17/03/2026

🔄 Previously, we showed that epithelial injury is common to glomerular diseases. Here we find similar patterns in diabetic, hypertensive and acute kidney disease, supporting a unified view of chronic kidney disease irrespective of initiating cause. doi.org/10.1101/2025...

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Saez-Rodriguez Group @saezlab.bsky.social · 17/03/2026

🔎 We identified shared cellular and molecular programs of acute and chronic injury that cut across both AKI and CKD – moving beyond clinical labels. Instead, they aligned with eGFR and histopathologic features like tubular atrophy and fibrosis.

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Saez-Rodriguez Group @saezlab.bsky.social · 17/03/2026

🧵 What does single-cell transcriptomics reveal about individual patients with acute (AKI) and chronic (CKD) kidney 🫘 disease? Can we use it to find new biomarkers? In our new preprint 👇, we asked this using biopsies from 150+ participants from the Kidney Precision Medicine Project.

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Saez-Rodriguez Group @saezlab.bsky.social · 12/03/2026

We further combine single-cell data with spatial transcriptomics to identify spatially constrained fibrotic cell signalling events shared across organs. All results are published as an open resource to support further discovery: organfibrosis.saezlab.org

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Saez-Rodriguez Group @saezlab.bsky.social · 12/03/2026

With our multi-level analysis, we first identify shared cell type-specific fibrotic programs within each organ. Then, we assess which parts of these gene programs are also shared across organs.

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Saez-Rodriguez Group @saezlab.bsky.social · 12/03/2026

In this study, we take a cross-organ view by integrating single-cell transcriptomic data from over 5 million cells across 20 studies, covering fibrotic diseases of the heart, liver, kidney, and lung. 🫁🫀

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Saez-Rodriguez Group @saezlab.bsky.social · 12/03/2026

🧵 See 👇 our new preprint on shared and organ-specific gene expression programs of fibrotic diseases 🧬 📄 Paper: doi.org/10.64898/202... 📊 Explore the data: organfibrosis.saezlab.org

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Saez-Rodriguez Group @saezlab.bsky.social · 12/03/2026

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Saez-Rodriguez Group @saezlab.bsky.social · 12/03/2026

With our multi-level analysis, we first identify shared cell type-specific fibrotic programs within each organ. Then, we assess which parts of these gene programs are also shared across organs.

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Saez-Rodriguez Group @saezlab.bsky.social · 12/03/2026

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Saez-Rodriguez Group @saezlab.bsky.social · 02/03/2026

Using these data, kinase–substrate interactions, and network inference methods, we tested how well different resources recover known (ground-truth) signaling interactions between kinases.

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Saez-Rodriguez Group @saezlab.bsky.social · 02/03/2026

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

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Saez-Rodriguez Group @saezlab.bsky.social · 02/03/2026

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.

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Saez-Rodriguez Group @saezlab.bsky.social · 25/02/2026

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

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Saez-Rodriguez Group @saezlab.bsky.social · 20/01/2026

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 🎉

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Saez-Rodriguez Group @saezlab.bsky.social · 15/01/2026

We recently posted a "2025 Publication Countdown" series on LinkedIn. See here ➡️ www.linkedin.com/company/saez...

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Saez-Rodriguez Group @saezlab.bsky.social · 17/12/2025

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

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Saez-Rodriguez Group @saezlab.bsky.social · 27/11/2025

🤗 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.

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Saez-Rodriguez Group @saezlab.bsky.social · 06/11/2025

New patients can be positioned on the map: In a cohort receiving LVADs (data from Kory Lavine’s lab), molecular changes in the map were consistent with clinical improvement, suggesting that the map may help characterize treatment responses.

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Saez-Rodriguez Group @saezlab.bsky.social · 06/11/2025

This allowed us to distinguish genes driven by compositional changes from those primarily affected by molecular regulation.

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Saez-Rodriguez Group @saezlab.bsky.social · 06/11/2025

We also uncovered a network of cell-type dependencies underlying these multicellular programs, with fibroblasts playing a central role, particularly coordinating with cardiomyocyte reprogramming (where we validated several ligand candidates consistent with this interaction).

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Saez-Rodriguez Group @saezlab.bsky.social · 06/11/2025

Using Multicellular Factor Analysis, a patient-level integration method (doi.org/10.7554/eLif...), we constructed a transcriptional patient map summarizing multicellular gene-expression variation in heart failure along two main axes.

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Saez-Rodriguez Group @saezlab.bsky.social · 06/11/2025

Across studies, gene-expression changes associated with heart failure showed a reproducible pattern in both bulk and single-nucleus data. Changes in cell-type composition were more variable, indicating that these two aspects of tissue remodelling may not always occur together.

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Saez-Rodriguez Group @saezlab.bsky.social · 06/11/2025

We curated an extensive compendium of >1500 patients profiled w bulk or single-nuc transcriptomics, building on our previous work tinyurl.com/sn6dxu95. This data engineering effort enabled the comparison and integration of insights to generate a reference of Heart Failure.

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Saez-Rodriguez Group @saezlab.bsky.social · 19/09/2025

🚨 New preprint We present an extended version of ScAPE, the method that won one of the prizes 🏆 in the @neuripsconf.bsky.social 2023 Single-Cell Perturbation Prediction challenge. 📄 preprint: doi.org/10.1101/2025... 🧬 code: github.com/scapeML/scape

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Saez-Rodriguez Group @saezlab.bsky.social · 17/09/2025

🤖✨ Dive into OmniPath Explorer - Interactively browse millions of annotations & hundreds of thousands of molecular interactions. Our new AI chat agent helps you query the database effortlessly, developed by Jonathan @jonsch.one!

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Saez-Rodriguez Group @saezlab.bsky.social · 17/09/2025

🥁 Check out our new preprint on OmniPath, the prior knowledge resource for #SystemsBiology, and its brand-new OmniPath Explorer web app! 🥳 📖 Preprint: www.biorxiv.org/content/10.1... 🔍 Explorer: explore.omnipathdb.org OmniPath integrates 160+ resources for multi-omics analysis & modeling. 🧶⬇️

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Saez-Rodriguez Group @saezlab.bsky.social · 15/09/2025

Introducing ParTIpy, a python package for Pareto Task Inference that scales to large-scale datasets, including single-cell and spatial transcriptomics. 🔗 Manuscript: www.biorxiv.org/content/10.1... 💻 Code: partipy.readthedocs.io

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Saez-Rodriguez Group @saezlab.bsky.social · 01/09/2025

👋 Time to say goodbye to another one of our PhD students, @smuellerdott.bsky.social. She was working on the integration of phosphoproteomics and transcriptomics data and will now join the Computational Oncology Team at Merck. We wish her all the best for this new chapter! 🚀 ✨

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Saez-Rodriguez Group @saezlab.bsky.social · 25/08/2025

🧑‍⚕️ Patient-level metadata analysis - PCA + ANOVA find metabolite drivers in patient subgroups - bioRCM spots distinct patterns; e.g., dipeptides in young vs. old kidney cancer patients ➡️ Insight into tumor microenvironment and potential biomarkers

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