Museum of spatial transcriptomics

By Lambda Moses, Lior S. Pachter. Nature Methods, 2020

1,032 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/f3913f94da0f6ac8591418a5451cbe4f02f54692

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In Molecular Biology

1. Roser Vento-Tormo
2. A. Haque
3. Cameron G. Williams
4. H. J. Lee
5. Takahiro Asatsuma
6. V. Swarup

Citations in the corpus

• An introduction to spatial transcriptomics for biomedical research (2022, methodology): “A recent review [17] identifies early steps towards these technologies as beginning in the 1960s, with labelling of nucleic acids via complementary probes in 1969 [37, 38], labelling of specific sequences in 1973 [39], and fluorescentlabelling in the late 70s [40, 41].”
• Methods and applications for single-cell and spatial multi-omics (2023, background): “Principles of spatial mono-omics methods for spatial multi-omics developments Methods for spatial mono-omics have progressed tremendously in the last decade with excellent reviews existing for spatial transcriptomics 165,171–173 , (epi)genomics 166,174 , proteomics 86,167 and metabolomics 168,175 .”
• hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data (2023, methodology): “These ENCODE VM23 comprehensive transcript set are shown below transcripts in (A) UMAP plot of 121,451 nuclei from the cortex of 22 ASD donors, 24 controls, and eight epilepsy donors profiledwith snRNA-seq.”