Searching journal content for articles similar to Miller et al. 31 (10): 1843.

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  1. Method: Deciphering context-specific gene programs from single-cell and spatial transcriptomics data with DeCEP
    • Lin Li,
    • Xianbin Su,
    • and Ze-Guang Han
    Genome Res. October 2025 35: 2300-2315; Published in Advance August 21, 2025, doi:10.1101/gr.279689.124
    .... Recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) technologies have empowered the comprehensive characterization of gene programs at both single-cell and spatial resolutions. Here, we present DeCEP, a computational framework designed to characterize context...
  2. Method: A model-based constrained deep learning clustering approach for spatially resolved single-cell data
    • Xiang Lin,
    • Le Gao,
    • Nathan Whitener,
    • Ashley Ahmed,
    • and Zhi Wei
    Genome Res. October 2022 32: 1906-1917; Published in Advance October 5, 2022, doi:10.1101/gr.276477.121
    ...41593-020-00787-0 ↵Miller BF, Bambah-Mukku D, Dulac C, Zhuang X, Fan J. 2021. Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with nonuniform cellular densities. Genome Res 31: 1843–1855. doi:10.1101/gr.271288.120 ↵Moncada R, Barkley D, Wagner...
  3. Method: A gene regulatory network–aware graph learning method for cell identity annotation in single-cell RNA-seq data
    • Mengyuan Zhao,
    • Jiawei Li,
    • Xiaoyi Liu,
    • Ke Ma,
    • Jijun Tang,
    • and Fei Guo
    Genome Res. July 2024 34: 1036-1051; Published in Advance August 12, 2024, doi:10.1101/gr.278439.123
    ....In single-cell transcriptome sequencing, high-resolution quantification of gene expression profiles provides insights into cellular heterogeneity and the molecular underpinnings of tissue phenotype variations (Kalucka et al. 2020; Argelaguet et al. 2021). Analyzing cell type composition using sc...
  4. Editorial: New frontiers in single-cell genomics
    • Nicholas E. Navin,
    • Orit Rozenblatt-Rosen,
    • and Nancy R. Zhang
    Genome Res. October 2021 31: ix-x; doi:10.1101/gr.276129.121
    ...– 1766 . 10.1101/gr.271874.120 Miller BF , Bambah-Mukku D , Dulac C , Zhuang X , Fan J . 2021 . Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomic data with nonuniform cellular densities . Genome Res (this issue) 31 : 1843 – 1855 . 10.1101/gr.271288...
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  5. Resource: Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains
    • Ekaterina Khrameeva,
    • Ilia Kurochkin,
    • Dingding Han,
    • Patricia Guijarro,
    • Sabina Kanton,
    • Malgorzata Santel,
    • Zhengzong Qian,
    • Shen Rong,
    • Pavel Mazin,
    • Marat Sabirov,
    • Matvei Bulat,
    • Olga Efimova,
    • Anna Tkachev,
    • Song Guo,
    • Chet C. Sherwood,
    • J. Gray Camp,
    • Svante Pääbo,
    • Barbara Treutlein,
    • and Philipp Khaitovich
    Genome Res. May 2020 30: 776-789; Published in Advance May 18, 2020, doi:10.1101/gr.256958.119
    ...subcortical regions in addition to the neocortical areas (Sousa et al. 2017a; Xu et al. 2018).Although the brain is composed of functionally diverse anatomical regions, each brain region is composed of multiple cell types (Lein et al. 2007). Single-cell RNA sequencing provides an opportunity to decompose gene...
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  6. Method: Scalable and model-free detection of spatial patterns and colocalization
    • Qi Liu,
    • Chih-Yuan Hsu,
    • and Yu Shyr
    Genome Res. September 2022 32: 1736-1745; Published in Advance September 9, 2022, doi:10.1101/gr.276851.122
    ...↵Miller BF, Bambah-Mukku D, Dulac C, Zhuang X, Fan J. 2021. Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomic data with nonuniform cellular densities. Genome Res 31: 1843–1855. doi:10.1101/gr.271288.120 ↵Miterko LN, White JJ, Lin T, Brown AM, O...
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  7. Method: Single-molecule long-read sequencing reveals the chromatin basis of gene expression
    • Yunhao Wang,
    • Anqi Wang,
    • Zujun Liu,
    • Andrew L. Thurman,
    • Linda S. Powers,
    • Meng Zou,
    • Yue Zhao,
    • Adam Hefel,
    • Yunyi Li,
    • Joseph Zabner,
    • and Kin Fai Au
    Genome Res. August 2019 29: 1329-1342; Published in Advance June 14, 2019, doi:10.1101/gr.251116.119
    ...and actively transcribed genes, at the single-cell level and in the long-range scale. The heterogeneous patterns of chromatin status spanning multiple genes were phased. Together with single-cell RNA-seq data, we quantitatively revealed how chromatin accessibility correlated with gene transcription positively...
    OPEN ACCESS ARTICLE
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