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Times Cited
Times Co-cited
Similarity
Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.
Patrik L Ståhl, Fredrik Salmén, Sanja Vickovic, Anna Lundmark, José Fernández Navarro, Jens Magnusson, Stefania Giacomello, Michaela Asp, Jakub O Westholm, Mikael Huss,[...]. Science 2016
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Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution.
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Samuel G Rodriques, Robert R Stickels, Aleksandrina Goeva, Carly A Martin, Evan Murray, Charles R Vanderburg, Joshua Welch, Linlin M Chen, Fei Chen, Evan Z Macosko. Science 2019
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Comprehensive Integration of Single-Cell Data.
Tim Stuart, Andrew Butler, Paul Hoffman, Christoph Hafemeister, Efthymia Papalexi, William M Mauck, Yuhan Hao, Marlon Stoeckius, Peter Smibert, Rahul Satija. Cell 2019
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Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH.
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High-definition spatial transcriptomics for in situ tissue profiling.
Sanja Vickovic, Gökcen Eraslan, Fredrik Salmén, Johanna Klughammer, Linnea Stenbeck, Denis Schapiro, Tarmo Äijö, Richard Bonneau, Ludvig Bergenstråhle, José Fernandéz Navarro,[...]. Nat Methods 2019
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RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells.
Kok Hao Chen, Alistair N Boettiger, Jeffrey R Moffitt, Siyuan Wang, Xiaowei Zhuang. Science 2015
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Three-dimensional intact-tissue sequencing of single-cell transcriptional states.
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Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas.
Reuben Moncada, Dalia Barkley, Florian Wagner, Marta Chiodin, Joseph C Devlin, Maayan Baron, Cristina H Hajdu, Diane M Simeone, Itai Yanai. Nat Biotechnol 2020
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Single-Cell Transcriptome Analysis Maps the Developmental Track of the Human Heart.
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Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity.
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Cells of the adult human heart.
Monika Litviňuková, Carlos Talavera-López, Henrike Maatz, Daniel Reichart, Catherine L Worth, Eric L Lindberg, Masatoshi Kanda, Krzysztof Polanski, Matthias Heinig, Michael Lee,[...]. Nature 2020
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Integrating single-cell transcriptomic data across different conditions, technologies, and species.
Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija. Nat Biotechnol 2018
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Spatial Transcriptomics and In Situ Sequencing to Study Alzheimer's Disease.
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Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis.
Silas Maniatis, Tarmo Äijö, Sanja Vickovic, Catherine Braine, Kristy Kang, Annelie Mollbrink, Delphine Fagegaltier, Žaneta Andrusivová, Sami Saarenpää, Gonzalo Saiz-Castro,[...]. Science 2019
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Fast, sensitive and accurate integration of single-cell data with Harmony.
Ilya Korsunsky, Nghia Millard, Jean Fan, Kamil Slowikowski, Fan Zhang, Kevin Wei, Yuriy Baglaenko, Michael Brenner, Po-Ru Loh, Soumya Raychaudhuri. Nat Methods 2019
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Single-cell in situ RNA profiling by sequential hybridization.
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Transcriptional and Cellular Diversity of the Human Heart.
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CellPhoneDB: inferring cell-cell communication from combined expression of multi-subunit ligand-receptor complexes.
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High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue.
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Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2.
Robert R Stickels, Evan Murray, Pawan Kumar, Jilong Li, Jamie L Marshall, Daniela J Di Bella, Paola Arlotta, Evan Z Macosko, Fei Chen. Nat Biotechnol 2021
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Spatially Resolved Transcriptomics Enables Dissection of Genetic Heterogeneity in Stage III Cutaneous Malignant Melanoma.
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Spatial reconstruction of single-cell gene expression data.
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Transcriptomic Profiling Maps Anatomically Patterned Subpopulations among Single Embryonic Cardiac Cells.
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Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography.
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mRNA-Seq whole-transcriptome analysis of a single cell.
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SpatialDE: identification of spatially variable genes.
Valentine Svensson, Sarah A Teichmann, Oliver Stegle. Nat Methods 2018
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In situ sequencing for RNA analysis in preserved tissue and cells.
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RNA velocity of single cells.
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Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression.
Chenglong Xia, Jean Fan, George Emanuel, Junjie Hao, Xiaowei Zhuang. Proc Natl Acad Sci U S A 2019
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Spatial organization of the somatosensory cortex revealed by osmFISH.
Simone Codeluppi, Lars E Borm, Amit Zeisel, Gioele La Manno, Josina A van Lunteren, Camilla I Svensson, Sten Linnarsson. Nat Methods 2018
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SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes.
Marc Elosua-Bayes, Paula Nieto, Elisabetta Mereu, Ivo Gut, Holger Heyn. Nucleic Acids Res 2021
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Robust decomposition of cell type mixtures in spatial transcriptomics.
Dylan M Cable, Evan Murray, Luli S Zou, Aleksandrina Goeva, Evan Z Macosko, Fei Chen, Rafael A Irizarry. Nat Biotechnol 2022
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Statistical analysis of spatial expression patterns for spatially resolved transcriptomic studies.
Shiquan Sun, Jiaqiang Zhu, Xiang Zhou. Nat Methods 2020
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Highly multiplexed subcellular RNA sequencing in situ.
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Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma.
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Massively parallel digital transcriptional profiling of single cells.
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Single-Cell Transcriptional Profiling Reveals Cellular Diversity and Intercommunication in the Mouse Heart.
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Visualization of single RNA transcripts in situ.
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Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.
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Simultaneous epitope and transcriptome measurement in single cells.
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SCENIC: single-cell regulatory network inference and clustering.
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Single-Cell Sequencing of the Healthy and Diseased Heart Reveals Cytoskeleton-Associated Protein 4 as a New Modulator of Fibroblasts Activation.
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Integrating spatial gene expression and breast tumour morphology via deep learning.
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Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.