SaeysLab
@saeyslab
Data mining and Modeling for Biomedicine, a VIB - UGent research unit
🚨 PhD candidate wanted! 🚨 We are looking for a talented computational scientist to join our thriving research team and work on clinical applications. Are you ready to apply your computational skills to make an impact on patient care? Apply now: jobso.id/kdfo
Honored to have received a CZI grant for further developing the cell-cell communication models of the future, together with "the other" @saezlab 😀 Really looking forward to this one ! @saeyslab @ChanZuckerberg
🎉 Congratulations to @YvanSaeys (@saeyslab @InflamResCen @ugent) for being awarded an EOSS grant from @ChanZuckerberg! Get ready for open-source cell-cell communication models. vibbio.tech/3zm0Xgv
Only 2 weeks left! ⏰ Don't hesitate and apply now for our Computational Cytometry Summer School if you want to know more about quality control, batch effect correction, clustering and statistical analysis of cytometry data 💡 Link below ⬇️
It's happening again! 🤩 Join us for a hands-on program designed for those interested in advancing their skills in computational cytometry data analysis. Find the program and apply here: t.ly/49QQe #CompCyto2025 🙏 to our sponsors @SonyBiotechInc and @BDBiosciences
We are thrilled to announce that SaeysLab is now officially a member of the EuroFlow Consortium! Through this collaboration, we will contribute to standardization of clinical cytometry workflows and data analysis (because we love consistent, accurate and reproducible results 😉).
It's happening again! 🤩 Join us for a hands-on program designed for those interested in advancing their skills in computational cytometry data analysis. Find the program and apply here: t.ly/49QQe #CompCyto2025 🙏 to our sponsors @SonyBiotechInc and @BDBiosciences

Final day of our SaeysLab conference! 👨🏫 Fascinating week where each subteam got to share their expertise with the other lab members: from cytometry over scRNA-seq to spatial omics. The machine learning team will top it all off with explainable AI and dimensionality reduction 🍰

What does the future of spatial omics data processing pipelines look like ? Meet Sparrow, our new human-in-the-loop interactive pipeline that facilitates better quality control, improves segmentation and leads to better downstream analysis @LottePollaris biorxiv.org/content/10.110…
@LottePollaris presenting the Sparrow pipeline. Fantastic collaboration between @saeyslab, @KC_DC_01 and our lab. Automated analysis of spatial omics data. How to annotate cells & correct for imaging artefacts. Fantastic presentation by this super talented PhD student 🤩🤩🤩👏🏻👏🏻
We celebrate the end of our three-day 🚀hackathon🚀 on spatial omics tools and methods in #Ghent #Belgium. A big thanks to all of the researchers across Europe. Check out our final slide deck and code! docs.google.com/presentation/d… github.com/saeyslab/VIB_H… #SpatialOmics24

Powering up for Day 2 of spatial omics hacking with our nice new @_VIB_AI coffee mugs #CoffeeToCode #SpatialOmics24 #FlandersAI

Our @VIBLifeSciences hackathon on spatial omics has 🚀 liftoff 🚀 ! 37 researchers of 30 institutes from 12 countries, coming together 3 days to create new tools and methods. hackmd.io/@berombau/BJet… #flandersai #SpatialOmics24

👇Our paper is now peer-reviewed and published in @eLife! We've also added a new case study on a Visium dataset of mouse melanoma. 📄 Read here: elifesciences.org/articles/88431 💻 GitHub repo: github.com/saeyslab/spotl…
(1/4) Our new benchmark on spatial deconvolution methods is now on @biorxiv_bioinfo (biorxiv.org/cgi/content/sh…)! We compared 11 methods on synthetic and real spatial transcriptomics data. You can run the methods using our containerized Nextflow pipeline at github.com/saeyslab/spotl…
Proud to present our work at #SIAMIS24. We show that classical compressed sensing techniques can be used to obtain a defense against adversarial perturbations that is not only very efficient but also has nice interpretable robustness guarantees. 💻🎆🙌arxiv.org/abs/2405.15971

🚨New paper published!🚨 We investigate 10 different quality metrics for attribution-based explanations on 8 image datasets, and use the results to propose a set of benchmarking guidelines. Read all about it here: doi.org/10.1007/s10994…

Interested in clustering cytometry data with FlowSOM, but not so fond of R? Check out Artuur Couckuyt's paper on translating FlowSOM to Python here: academic.oup.com/bioinformatics…
