SiGra: single-cell spatial elucidation through an image-augmented graph transformer

[1]  Zachary R. Lewis,et al.  High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging. , 2022, Nature biotechnology.

[2]  John R. Haliburton,et al.  Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing , 2022, Life Science Alliance.

[3]  E. Lundberg,et al.  The emerging landscape of spatial profiling technologies , 2022, Nature Reviews Genetics.

[4]  Keely A. Dulmage,et al.  Transcriptional profiling of single tumour cells from pleural effusions reveals heterogeneity of epithelial to mesenchymal transition and extra‐cellular matrix marker expression , 2022, Clinical and translational medicine.

[5]  Brian R. Long,et al.  Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH , 2022, Science.

[6]  Lani F. Wu,et al.  Integrative spatial analysis of cell morphologies and transcriptional states with MUSE , 2022, Nature Biotechnology.

[7]  Fabian J Theis,et al.  Spatial components of molecular tissue biology , 2022, Nature Biotechnology.

[8]  A. Arnsten,et al.  Unusual Molecular Regulation of Dorsolateral Prefrontal Cortex Layer III Synapses Increases Vulnerability to Genetic and Environmental Insults in Schizophrenia , 2022, Biological Psychiatry.

[9]  Mingyao Li,et al.  SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network , 2021, Nature Methods.

[10]  Shihua Zhang,et al.  Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder , 2021, Nature Communications.

[11]  K. Rogers,et al.  Spatial omics and multiplexed imaging to explore cancer biology , 2021, Nature Methods.

[12]  C. Jørgensen,et al.  Single-cell analysis defines a pancreatic fibroblast lineage that supports anti-tumor immunity , 2021, Cancer cell.

[13]  H. Kang,et al.  Microscopic examination of spatial transcriptome using Seq-Scope , 2021, Cell.

[14]  Raphael Gottardo,et al.  Spatial transcriptomics at subspot resolution with BayesSpace , 2021, Nature Biotechnology.

[15]  Jacqueline M. Roberts,et al.  Transcriptional repression by FEZF2 restricts alternative identities of cortical projection neurons , 2021, Cell reports.

[16]  Hui Yu,et al.  A review on the attention mechanism of deep learning , 2021, Neurocomputing.

[17]  Huanming Yang,et al.  Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays , 2021, Cell.

[18]  Raphael Gottardo,et al.  Integrated analysis of multimodal single-cell data , 2020, Cell.

[19]  Yu Sun,et al.  Masked Label Prediction: Unified Massage Passing Model for Semi-Supervised Classification , 2020, IJCAI.

[20]  L. Pachter,et al.  Museum of spatial transcriptomics , 2020, Nature Methods.

[21]  Irving L. Weissman,et al.  A single-cell transcriptomic atlas characterizes ageing tissues in the mouse , 2020, Nature.

[22]  Edward S Boyden,et al.  Expansion sequencing: Spatially precise in situ transcriptomics in intact biological systems , 2020, Science.

[23]  J. Kleinman,et al.  Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex , 2020, Nature Neuroscience.

[24]  T. Low,et al.  Revisiting the Roles of Pro-Metastatic EpCAM in Cancer , 2020, Biomolecules.

[25]  Philipp S. Hoppe,et al.  AXIN2+ Pericentral Hepatocytes Have Limited Contributions to Liver Homeostasis and Regeneration. , 2019, Cell stem cell.

[26]  Fabian V. Filipp,et al.  Opportunities for Artificial Intelligence in Advancing Precision Medicine , 2019, Current Genetic Medicine Reports.

[27]  Roland Eils,et al.  Cell segmentation-free inference of cell types from in situ transcriptomics data , 2019, Nature Communications.

[28]  Sara Shirowzhan,et al.  Spatial Analysis Using Temporal Point Clouds in Advanced GIS: Methods for Ground Elevation Extraction in Slant Areas and Building Classifications , 2019, ISPRS Int. J. Geo Inf..

[29]  Mary Regina Boland,et al.  Preparing next-generation scientists for biomedical big data: artificial intelligence approaches. , 2019, Personalized medicine.

[30]  Vincent A. Traag,et al.  From Louvain to Leiden: guaranteeing well-connected communities , 2018, Scientific Reports.

[31]  James T. Webber,et al.  Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris , 2018, Nature.

[32]  Patrik L. Ståhl,et al.  Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity , 2018, Nature Communications.

[33]  Fabian J Theis,et al.  SCANPY: large-scale single-cell gene expression data analysis , 2018, Genome Biology.

[34]  Allon M. Klein,et al.  Single-Cell Analysis of Experience-Dependent Transcriptomic States in Mouse Visual Cortex , 2017, Nature Neuroscience.

[35]  D. Levy,et al.  Whole blood gene expression and white matter Hyperintensities , 2017, Molecular Neurodegeneration.

[36]  D. Zeldin,et al.  Characterization of the Tissue Distribution of the Mouse Cyp2c Subfamily by Quantitative PCR Analysis , 2017, Drug Metabolism and Disposition.

[37]  Andrey Alexeyenko,et al.  Spatially resolved transcriptome profiling in model plant species , 2017, Nature Plants.

[38]  S. Haberichter von Willebrand factor propeptide: biology and clinical utility. , 2015, Blood.

[39]  Ting Liu,et al.  Matrix Gla protein regulates differentiation of endothelial cells derived from mouse embryonic stem cells , 2015, Angiogenesis.

[40]  Piero Carninci,et al.  A draft network of ligand–receptor-mediated multicellular signalling in human , 2015, Nature Communications.

[41]  S. Linnarsson,et al.  Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq , 2015, Science.

[42]  Daixing Zhou,et al.  Increased expression of SOX4 is a biomarker for malignant status and poor prognosis in patients with non-small cell lung cancer , 2015, Molecular and Cellular Biochemistry.

[43]  Alexander van Oudenaarden,et al.  Spatially resolved transcriptomics and beyond , 2014, Nature Reviews Genetics.

[44]  V. Martínez‐Cerdeño,et al.  RELN-expressing neuron density in layer I of the superior temporal lobe is similar in human brains with autism and in age-matched controls , 2014, Neuroscience Letters.

[45]  Adam J Pawson,et al.  IUPHAR-DB: updated database content and new features , 2012, Nucleic Acids Res..

[46]  C. Levelt,et al.  Synaptotagmin-2 Is a Reliable Marker for Parvalbumin Positive Inhibitory Boutons in the Mouse Visual Cortex , 2012, PloS one.

[47]  J. Woulfe,et al.  Lipofuscin and aging: a matter of toxic waste. , 2005, Science of aging knowledge environment : SAGE KE.

[48]  Izhar Ben-Shlomo,et al.  Signaling Receptome: A Genomic and Evolutionary Perspective of Plasma Membrane Receptors Involved in Signal Transduction , 2003, Science's STKE.

[49]  David Eisenberg,et al.  Bioinformatic identification of potential autocrine signaling loops in cancers from gene expression profiles , 2001, Nature Genetics.

[50]  Michael F. Goodchild,et al.  Integrating GIS and spatial data analysis: problems and possibilities , 1992, Int. J. Geogr. Inf. Sci..