SwePub
Tyck till om SwePub Sök här!
Sök i SwePub databas

  Extended search

Träfflista för sökning "WFRF:(Borg Åke) ;hsvcat:2;lar1:(lu)"

Search: WFRF:(Borg Åke) > Engineering and Technology > Lund University

  • Result 1-2 of 2
Sort/group result
   
EnumerationReferenceCoverFind
1.
  • He, B., et al. (author)
  • Integrating spatial gene expression and breast tumour morphology via deep learning
  • 2020
  • In: Nature Biomedical Engineering. - : Nature Research. - 2157-846X. ; 4:8, s. 827-834
  • Journal article (peer-reviewed)abstract
    • Spatial transcriptomics allows for the measurement of RNA abundance at a high spatial resolution, making it possible to systematically link the morphology of cellular neighbourhoods and spatially localized gene expression. Here, we report the development of a deep learning algorithm for the prediction of local gene expression from haematoxylin-and-eosin-stained histopathology images using a new dataset of 30,612 spatially resolved gene expression data matched to histopathology images from 23 patients with breast cancer. We identified over 100 genes, including known breast cancer biomarkers of intratumoral heterogeneity and the co-localization of tumour growth and immune activation, the expression of which can be predicted from the histopathology images at a resolution of 100 µm. We also show that the algorithm generalizes well to The Cancer Genome Atlas and to other breast cancer gene expression datasets without the need for re-training. Predicting the spatially resolved transcriptome of a tissue directly from tissue images may enable image-based screening for molecular biomarkers with spatial variation. 
  •  
2.
  • Vickovic, Sanja, et al. (author)
  • High-definition spatial transcriptomics for in situ tissue profiling
  • 2019
  • In: Nature Methods. - : NATURE PUBLISHING GROUP. - 1548-7091 .- 1548-7105. ; 16:10, s. 987-
  • Journal article (peer-reviewed)abstract
    • Spatial and molecular characteristics determine tissue function, yet high-resolution methods to capture both concurrently are lacking. Here, we developed high-definition spatial transcriptomics, which captures RNA from histological tissue sections on a dense, spatially barcoded bead array. Each experiment recovers several hundred thousand transcriptcoupled spatial barcodes at 2-mu m resolution, as demonstrated in mouse brain and primary breast cancer. This opens the way to high-resolution spatial analysis of cells and tissues.
  •  
Skapa referenser, mejla, bekava och länka
  • Result 1-2 of 2

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view