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Bioinformatics (Oxford, England)
|
March 11, 2021
sepal: identifying transcript profiles with spatial patterns by diffusion-based modeling
Alma Andersson, Joakim Lundeberg
Nature Methods
|
March 4, 2024
Spatial landmark detection and tissue registration with deep learning
Markus Ekvall, Ludvig Bergenstråhle, Alma Andersson, et al.
Plos Computational Biology
|
October 7, 2022
Markov state modelling reveals heterogeneous drug-inhibition mechanism of Calmodulin
Annie M Westerlund, Akshay Sridhar, Leo Dahl, et al.
Communications Biology
|
October 10, 2020
Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography
Alma Andersson, Joseph Bergenstråhle, Michaela Asp, et al.
Nature Biomedical Engineering
|
June 24, 2020
Integrating spatial gene expression and breast tumour morphology via deep learning
Bryan He, Ludvig Bergenstråhle, Linnea Stenbeck, et al.
Cell Metabolism
|
November 3, 2021
Spatial mapping reveals human adipocyte subpopulations with distinct sensitivities to insulin
Jesper Bäckdahl, Lovisa Franzén, Lucas Massier, et al.
Cell Metabolism
|
August 11, 2021
Spatial mapping reveals human adipocyte subpopulations with distinct sensitivities to insulin
Jesper Bäckdahl, Lovisa Franzén, Lucas Massier, et al.
Nature Communications
|
December 3, 2021
Spatial Transcriptomics to define transcriptional patterns of zonation and structural components in the mouse liver
Franziska Hildebrandt, Alma Andersson, Sami Saarenpää, et al.
Nature Communications
|
October 15, 2021
Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions
Alma Andersson, Ludvig Larsson, Linnea Stenbeck, et al.
Nature Biotechnology
|
November 30, 2021
Super-resolved spatial transcriptomics by deep data fusion
Ludvig Bergenstråhle, Bryan He, Joseph Bergenstråhle, et al.
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Search research articles
Search
Showing results (1-10 of 19) with videos related to
Sort By:
Page
of 2
Bioinformatics (Oxford, England)
|
March 11, 2021
sepal: identifying transcript profiles with spatial patterns by diffusion-based modeling
Alma Andersson, Joakim Lundeberg
Nature Methods
|
March 4, 2024
Spatial landmark detection and tissue registration with deep learning
Markus Ekvall, Ludvig Bergenstråhle, Alma Andersson, et al.
Plos Computational Biology
|
October 7, 2022
Markov state modelling reveals heterogeneous drug-inhibition mechanism of Calmodulin
Annie M Westerlund, Akshay Sridhar, Leo Dahl, et al.
Communications Biology
|
October 10, 2020
Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography
Alma Andersson, Joseph Bergenstråhle, Michaela Asp, et al.
Nature Biomedical Engineering
|
June 24, 2020
Integrating spatial gene expression and breast tumour morphology via deep learning
Bryan He, Ludvig Bergenstråhle, Linnea Stenbeck, et al.
Cell Metabolism
|
November 3, 2021
Spatial mapping reveals human adipocyte subpopulations with distinct sensitivities to insulin
Jesper Bäckdahl, Lovisa Franzén, Lucas Massier, et al.
Cell Metabolism
|
August 11, 2021
Spatial mapping reveals human adipocyte subpopulations with distinct sensitivities to insulin
Jesper Bäckdahl, Lovisa Franzén, Lucas Massier, et al.
Nature Communications
|
December 3, 2021
Spatial Transcriptomics to define transcriptional patterns of zonation and structural components in the mouse liver
Franziska Hildebrandt, Alma Andersson, Sami Saarenpää, et al.
Nature Communications
|
October 15, 2021
Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions
Alma Andersson, Ludvig Larsson, Linnea Stenbeck, et al.
Nature Biotechnology
|
November 30, 2021
Super-resolved spatial transcriptomics by deep data fusion
Ludvig Bergenstråhle, Bryan He, Joseph Bergenstråhle, et al.
Page
of 2