Gain practical experience using widely adopted tools and resources to apply causal techniques in real-world biomedical contexts. Applications are now open until 21 June. Grants and bursaries are available for this @embo.org Practical Course: www.ebi.ac.uk/training/eve... 🧬🖥️💊📊

Now you can plot cool networks using DOT and graphviz layouts. It does not matter if graphviz is not installed, it supports native binaries, js/wasm and webassembly with wasmtime, + other nice options! Check the @marimo.io notebook in molab: molab.marimo.io/notebooks/nb...

marimo | easydot-graphviz - molab

marimo notebook by Pablo in Pablo Rodríguez Mier's Workspace

molab.marimo.io

Don't be shy to take on a little two-week side project. These five months will be the most precious three years of your academic journey.

Need to visualize complex graphs, trees, or workflows in Python? easydot renders Graphviz diagrams in the browser with a single line of code. No binary install required. Plays nicely with @marimo.io notebooks too! 📦 github.com/pablormier/easydot ▶️ demo: marimo.app/l/y20xye

GitHub - pablormier/easydot: Graphviz in the browser. Zero installs. One line of Python.

Graphviz in the browser. Zero installs. One line of Python. - pablormier/easydot

github.com

Causality in biomedicine: going beyond associations is organised by: @avakhamseh.bsky.social @sjoerdvbeentjes.bsky.social @pablormier.bsky.social Apply by 21 June: www.ebi.ac.uk/training/eve... 🧬🖥️💊📊

🧵 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

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...

Benchmarking EGF signaling pathway inference using phosphoproteomics and kinase-substrate interactions - Nature Communications

To what extent can large-scale approaches accurately reconstruct classic signaling pathways? Here, authors revisit the EGF pathway using phosphoproteomics and kinase-substrate interactions

doi.org

Remember the slogan projects used to have: "Made with ❤️ by XYZ"? Soon we’ll start seeing: "Made by humans for humans"

I'm teaching Statistical Rethinking again starting Jan 2026. This time with live lectures, divided into Beginner and Experienced sections. Will be a lot more work for me, but I hope much better for students. I will record lectures & all will be found at this link: github.com/rmcelreath/s...

Unifying multi-sample network inference from prior knowledge and omics data with CORNETO ->Nature | #Data | More info from EcoSearch

Unifying multi-sample network inference from prior knowledge and omics data with CORNETO

Mixed-integer optimization Mixed-integer programming is a type of constrained optimization problem that involves decision variables that can be both integer and continuous. A mixed-integer programming problem can be defined as follows: $$\begin{array}{ll}\mathop{\min }\limits_{{\bf{x}}\in {{\mathbb{R}}}^{n},\,{\bf{y}}\in {{\mathbb{Z}}}^{m}}&f({\bf{x}},{\bf{y}})\\ \,\text{subject to}\,&{g}_{i}({\bf{x}},{\bf{y}})\le 0,\quad i=1,2,\ldots ,k,\\...

nature.com

🚨 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

ScAPE: A lightweight multitask learning baseline method to predict transcriptomic responses to perturbations https://www.biorxiv.org/content/10.1101/2025.09.08.674873v1

We present our MetaProViz #Rpackage for #metabolomics analysis & prior knowledge integration to generate mechanistic hypotheses on how metabolic changes affect metabolite classes, pathways & environment interaction 🔗 www.biorxiv.org/content/10.1... 📦 saezlab.github.io/MetaProViz/ 🧵 Thread ⬇️

New course announced! We're thrilled to be hosting the @embo.org Practical Course 'Causality in biomedicine: going beyond associations' from 4 – 9 October 2026. Register your interest and be the first to hear when the course opens for applications: www.ebi.ac.uk/training/eve...

New course “EMBO Causality in Biomedicine”: We have organised the first EMBO course in *causal* stats/ML methods for quantitative biomedicine. @sjoerdvbeentjes.bsky.social @nimahejazi.org @pablormier.bsky.social @DariaSokolova @CarolineUhler Very much looking forward to teaching and discussing!

EMBL-EBI Training@training.ebi.embl.org · last yr.

New course announced! We're thrilled to be hosting the @embo.org Practical Course 'Causality in biomedicine: going beyond associations' from 4 – 9 October 2026. Register your interest and be the first to hear when the course opens for applications: www.ebi.ac.uk/training/eve...

This project has been in the making for quite some time. CORNETO not only integrates key concepts and methodologies in biological network inference, but also introduces a novel framework for multi-condition analysis. Congrats to the team, and especially to @pablormier.bsky.social for leading this.

Saez-Rodriguez Group@saezlab.bsky.social · last yr.

🎉 The revised version of CORNETO, our unified Python framework for knowledge-driven network inference from omics data, is published in peer reviewed form 🔗 Paper: www.nature.com/articles/s42... 📖 News & Views: www.nature.com/articles/s42... 💻 Code: corneto.org 🧵 Thread 👇

🎉 The revised version of CORNETO, our unified Python framework for knowledge-driven network inference from omics data, is published in peer reviewed form 🔗 Paper: www.nature.com/articles/s42... 📖 News & Views: www.nature.com/articles/s42... 💻 Code: corneto.org 🧵 Thread 👇

How can we find out what’s really going on inside cells when we’re generating so much complex data? CORNETO is an open-source tool that uses machine learning to turn tangled omics datasets into clear maps of how genes, proteins, and signalling pathways interact. www.ebi.ac.uk/about/news/r... 🧪

CORNETO: machine learning to decode complex omics data

New tool combines biological knowledge with machine learning to help researchers extract meaningful insights from complex omics data.

ebi.ac.uk

The latest version of the Kasumi manuscript is now published in Nature Comms www.nature.com/articles/s41... Kasumi identifies patterns in tissue patches, enabling analysis of disease progression and treatment response while providing insights into spatial coordination at cell-type or marker level

Learning tissue representation by identification of persistent local patterns in spatial omics data - Nature Communications

Spatial omics reveal tissue structures and can aid patient stratification. The authors present a method to identify patterns in tissue patches, enabling analysis of disease progression and treatment r...

nature.com

🚨 New preprint: Topography Aware Optimal Transport for Alignment of Spatial Omics Data We present our new alignment framework TOAST www.biorxiv.org/content/10.1...

Turns out the way we usually pre-train foundational cell models adds very little information to the system - definitely not enough to make drug effect predictions work. Not what I've expected. #virtualcells #foundationalmodels #compbio blog.turbine.ai/p/pretrainin...

Pretraining virtual cells is useless

the way we do it now

blog.turbine.ai

📄 Update on our preprint about Gene Regulatory Net (GRN) benchmarking 📄 We have included the original and decoupled version of SCENIC+, added a new metric and two more databases. Dictys and SCENIC+ outperformed others, but still performed poorly in causal mechanistic tasks. doi.org/10.1101/2024... 👇

Saez-Rodriguez Group@saezlab.bsky.social · 2y ago

We present Gene Regulatory nETwork Analsyis (GRETA), a framework to infer, compare and evaluate gene regulatory networks #GRNs. With it, we have benchmarked multimodal and unimodal GRN inference methods. Check the results here 👇 Paper: doi.org/10.1101/2024.12.20.629764 Code: github.com/saezlab/greta

Haha, Peyman Milanfar blocked me within milliseconds after I liked a reply of somebody else defending @hardmaru.bsky.social and Sakana AI against his attacks. Fastest block ever!

Stephen Boyd's reaction when a student says they're using Genetic Algorithms for optimization is priceless 😂 youtu.be/kV1ru-Inzl4?...

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 1

YouTube video by Stanford Online

youtu.be

In many countries we're seeing voters that have never known anything other than stability and a certain level of competence voting for anti- system candidates because they have convinced themselves of two things: things right now are awful; change will only be for the better.

This is also why vaccine-denial is so prevalent. People don’t have a memory of what mass death from smallpox looked like, or post-poli disability.

No AGI until LLMs can reliably produce useful LaTeX. Haven’t seen one that truly delivers. We need a LLM LaTeX benchmark!

"LLaDA: Large Language Diffusion Models" Nie et al. Just read this fascinating paper. Scaled up Masked Diffusion Language Models to 8B params, and show that it can match #LLMs (including Llama 3) while solving some key limitations! Let's dive in... 🧵 (1/8) #genai

We are delighted to announce The Health Privacy Challenge, an interactive opportunity for advancement at the intersection of computational biology and privacy research, brought to you as a part of CAMDA Conference at #ISMB/ECCB2025 🫐🍅 Register to participate: benchmarks.elsa-ai.eu?ch=4