Chen, Kh, Boettir, An, Moffitt, Jr, Wang, S. & Zhuang, X. Science 348AAA6090 (2015).
Shah, S., Lubeck, E., Zhou, W. & Cai, L. reveals the spatial organization of cells in the mouse hippocampus. Neuron 92342-357 (2016).
Ståhl, PL et al. Visualization and analysis of gene expression in spatial transcriptomic and tissue sections. Science 35378-82 (2016).
Wang, X. et al. Three -dimensional robust tissue sequence of single -celled transcriptional conditions. Science 361EAAT5691 (2018).
Rodriques, SG et al. Slide-Seq: A scalable technology to measure the expression of genome-diameter at high spatial resolution. Science 3631463–1467 (2019).
MOSES, L. & Pachter, L. Spatial Transcriptomic Museum. NAT. Method 19534-546 (2022).
Liu, Y. et al. High spatial resolution multi-comic sequence through deterministic barcoding in tissue. Cell 1831665-1681 (2020).
Lieberman-Baid, E. et al. The comprehensive map of long -range interactions reveals the folding principles of the human genome. Science 326289-293 (2009).
The singer, A. A statement on global positioning from local distances. Proc. Natl Acad. Sci. America 1059507–9511 (2008).
Novembre, J. et al. Genes reflect geography in Europe. Nature 45698-101 (2008).
Glaser, Ji, Zamft, UN, Church, GM & Cording, KP Puzzle Imaging: Using large -scale dimensional reduction algorithms for localization. Plos One 10E0131593 (2015).
Boulgakov brings AA, Ellington, AD & Marcotte, Em, microscopy to see the order. Trends biotechnol. 38154-162 (2020).
Weinstein, JA, REGEV, A. & Zhang, F. DNA Microscopy: Spatio-Genetic imaging with optical reaction alone with a chemical reaction. Cell 178229–241.E16 (2019).
Weinstein, Ja and Qian, N. Voluctive imaging of a solid organism by a distributed molecular network. Stand out Biorxiv https://doi.org/10.1101/2023.08.11.553025 (2023).
Hoffecker, It, Yang, Y., Bernardinelli, G., Orponen, P. & Högberg, B. Proc. Natl Acad. Sci. America 11619282–19287 (2019).
Greenstreet, L. et al. DNA-GPs: The theoretical framework for the synthesis of spatial genomic and existing methods. Cell system. 14844-859.E4 (2023).
McINES, L., Healy, J. & Melville, J. Umap: Uniform manifold approach and projection for dimension reduction. Stand out Arxiv https://doi.org/10.48550/arxiv.1802.03426 (2018).
Stickels, RR et al. Slide-seqv2 with extremely sensitive spatial transcriptomic in the close resolution of the cell. NAT. Biotechnol. 39313-319 (2021).
Cable, DM et al. Robust decomposition of cell type mixtures in spatial transcriptomics. NAT. Biotechnol. 40517-526 (2022).
Russell, Ajc et al. The slide tag provides single nucleus barcoding for multimodal spatial genomic. Nature 625101-109 (2024).
Yu, T. et al. Unlike sensory neurons defined as phenotypic, transcripts expressed. J. Comp. Neurol. 483251-262 (2005).
Cable, DM et al. Inference of the cell type of differential expression in spatial transcriptomic. NAT. Method 191076-1087 (2022).
Becht, E. et al. Dimensional reduction for visualization of single -celled data using UMAP. NAT. Biotechnol. 3738-44 (2019).
Kajihara, T. et al. Recording of non -rigid of serial section images by mixing transformations for 3D restructuring. Description definition of pattern. 96106956 (2019).
Lee, BC, Tward, DJ, MITRA, PP & Miller, MI, Calculated anatomy randomly orbiting model using a sobolavis on the whole brain serial section histology on variational solutions. Plos Comput. Biol. 14E1006610 (2018).
Virtanen, P. et al. SCIPY 1.0: Basic algorithms for scientific information processing in Python. NAT. Method 17261-272 (2020).
Nolelet, CJ et al. GPU accelerates the speed of light with the GPU acceleration. Inside Proc. AAAI conf. Artifet. Mind. Vol. 35, 418-426 (AAAI Press, 2021).
Palla, G. et al. Squidpy: Scalable frame for spatial Omics analysis. NAT. Method 19171-178 (2022).
ZHENG, GXY et al. Parallel digital transcriptional profile of single cells. NAT. Commune. 814049 (2017).
Fleming, SJ et al. Unprinted extraction of systematic background noise from droplet -based single -celled experiments using Cellbender. NAT. Method 201323–1335 (2023).
Qiu, C. et al. A single -celled mouse prenatal development from Gastrula to birth. Nature 6261084-1093 (2024).
Hu, C. et al. Scalable spatial transcriptomic through computational array reconstruction. Data sets. NCBI SRA. https://www.ncbi.nlm.nih.gov/sra/prjna1221542 (2025).
Hu, C. et al. Scalable spatial transcriptomic through computational array reconstruction. Source code. Gitithub https://github.com/chenlei-hu/slide_recon (2024).
