Jovan Tanevski
@tanevski.bsky.social
Group leader - computational biomedical discovery. Heidelberg University & Heidelberg University Hospital. https://www.tanevskilab.org
computational scientific discovery, biomedicine, spatial omics
computational scientific discovery, biomedicine, spatial omics
This work was led by Francesco Ceccarelli in collaboration with Pietro Liò, Sean B. Holden, @saezlab.bsky.social and Tanevski Lab.
April 22, 2025 at 9:37 AM
This work was led by Francesco Ceccarelli in collaboration with Pietro Liò, Sean B. Holden, @saezlab.bsky.social and Tanevski Lab.
We demonstrate TOAST on tasks of intra-, intersample, and temporal alignment in:
🧠 Human cortical layers (Visium)
🧫 Axolotl regeneration (Stereo-seq)
🐭 Locallization in mouse embryo development (seqFISH)
🎯 Various cancer types (IMC)
... with state-of-the-art efficiency and performance.
🧠 Human cortical layers (Visium)
🧫 Axolotl regeneration (Stereo-seq)
🐭 Locallization in mouse embryo development (seqFISH)
🎯 Various cancer types (IMC)
... with state-of-the-art efficiency and performance.
April 22, 2025 at 9:37 AM
We demonstrate TOAST on tasks of intra-, intersample, and temporal alignment in:
🧠 Human cortical layers (Visium)
🧫 Axolotl regeneration (Stereo-seq)
🐭 Locallization in mouse embryo development (seqFISH)
🎯 Various cancer types (IMC)
... with state-of-the-art efficiency and performance.
🧠 Human cortical layers (Visium)
🧫 Axolotl regeneration (Stereo-seq)
🐭 Locallization in mouse embryo development (seqFISH)
🎯 Various cancer types (IMC)
... with state-of-the-art efficiency and performance.
TOAST quantifies spatial coherence using entropy in local neighborhoods—favoring alignments that keep the order of local spatial compositions. It also preserves neighborhood consistency—aligning spots with similar gene expression in the spatial neighborhood.
April 22, 2025 at 9:37 AM
TOAST quantifies spatial coherence using entropy in local neighborhoods—favoring alignments that keep the order of local spatial compositions. It also preserves neighborhood consistency—aligning spots with similar gene expression in the spatial neighborhood.
Alignment is an important step for data integration and transfer of information that can help gain insights into mechanisms, progression and structural changes in disease. When the spatial context is available it *has to* complement molecular similarity to yield more biologically plausible mappings.
April 22, 2025 at 9:37 AM
Alignment is an important step for data integration and transfer of information that can help gain insights into mechanisms, progression and structural changes in disease. When the spatial context is available it *has to* complement molecular similarity to yield more biologically plausible mappings.