So happy to see that spage2vec works so well to find cell niches from spatially multiplexed single cell data! Congrats @lesolorzanova (and all others) for this very interesting work!
The latest version of umap-learn is now out. Version 0.5 includes some major new features, including ParametricUMAP, DensMAP, AlignedUMAP, model composition, and model updating. Thank you to everyone who contributed! 1/14
Excited to share our data&model zoo sfaira: We provide 233 data sets, 55 organs, 3.1M annotated cells together with 8 pre-trained model classes, to replace manual workflows, facilitate method benchmarking & extension w private data. https://t.co/4b8HfbGR24 https://t.co/E14NUfSiJl
#CoMIR: Contrastive Multimodal Image Representation for Registration @ #NeurIPS2020 – solving your #multimodal#imageRegistration needs by first translating images to a shared virtual modality where the task is easier: https://t.co/PUsjkKjD9Q
https://t.co/BZdd8RNhcK
#MIDAgroup
Come by my poster at #I2K2020 if you want to learn about how to visualize millions of in situ sequencing gene expression points and how you can use them to learn more about your cell types and spatial compartments! @Vi2UU @CarolinaWahlby@gapartel
Proud of @gapartel presenting his dissertation at @Vi2UU. Image and data analysis for spatial resolved transcriptomics. Extremely powerful, bleeding edge technology for exploring the very thing we are all made of. We thank the great opponent Roland Eils @CaptainSysBio
Out now: automated, unsupervised and unbiased annotation of spatial compartments from in situ sequencing data. https://t.co/0RXTAYfnPl @gapartel@CarolinaWahlby@M_Hilscher
🔬 Different microscopes output different image file formats making it challenging for scientists to compare. That's why we developed an #openscience software to help level the playfield. #microscopy
https://t.co/QjZzixBqt5
Our #TissUUmaps applications note is out! and it's Open access! We thank @OUPBioinfo for a friendly process, the reviewers for their kind comments and constructive criticism, @UppsalaUniLib for the OA agreements and @ERC_Research for the funding. @CarolinaWahlby @GabrielePartel
A scalable embedding algorithm that clusters scRNA-seq data by optimizing a clustering objective function and enables batch effects removal, from @DrMingyaoLi@UPennDBEI@KSusztak
https://t.co/QxYqwSy8vE
Phew, so much work! But finally submitted another paper. If you want to hear me embarrassing myself speaking english go to
https://t.co/W3F7tAuQch
You can also visit if you are curious about our work! #TissUUmaps#geneExpression#spatialTranscriptomics
L’unità e il lavoro di squadra sono da sempre i principi su cui si fonda la nostra Forza Armata e, in questo momento più che mai, sono fondamentali.
Ed allora, come fanno da sempre le @FrecceTricolori ‘facciamo squadra’ 💪🏻, uniamo le forze 🏋🏻, insieme ce la faremo 🇮🇹!
Teaching online the next few weeks? Check out this Coding & Vision 101 Educational Lecture Series includes 12 videos produced by the Allen Institute for Brain Science to serve as an educational resource for the community.
https://t.co/4I5flwyzsE
Two open positions (senior + postdoc) in digital image processing with life science applications in my lab at Uppsala University and SciLifeLab:
https://t.co/HMTEKifIBq
https://t.co/gRcGRRYUuL
#WahlbyLab#SciLifeLab