Searching journal content for articles similar to Ding et al. 28 (3): 383.

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  1. Method: Recovering gene regulatory networks in single-cell multi-omics data with PRISM-GRN
    • Wenhao Zhang,
    • Lan Cao,
    • Xiaoxuan Gu,
    • Yongyu Long,
    • and Ying Wang
    Genome Res. January 2026 36: 142-158; Published in Advance October 9, 2025, doi:10.1101/gr.280757.125
    ...for reconstructing cell type–specific GRNs based on single-cell multi-omics. Based on the aforementioned gene expression principle, PRISM-GRN incorporates a biologically interpretable architecture into the probabilistic framework, which is shown in Figure 1B. By integrating gene expression profiles, chromatin...
  2. Method: Polyomino reconstructs spatial transcriptomic profiles with single-cell resolution via a region-allocation method
    • Quanyou Cai,
    • Lihui Lin,
    • Xin Liu,
    • and Jiekai Chen
    Genome Res. November 2025 35: 2513-2526; Published in Advance October 22, 2025, doi:10.1101/gr.280532.125
    .... After applying Polyomino for single-cell-to-space mapping, we assessed the recovery of these genes by calculating the Pearson correlation coefficient (PCC) between the original and reconstructed expression values. We also visualized the spatial expression patterns for each marker gene before dropout...
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  3. 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
    ...cellular contexts in single-cell RNA sequencing (scRNA-seq) data. Based on the topology of these functional networks, DeCEP identifies context-dependent hub genes, calculates DeCEP scores, and determines the states of individual cells. (B) DeCEP anchors cell states to spatial locations in spatial...
  4. Method: A unified analysis of atlas single-cell data
    • Hao Chen,
    • Nam D. Nguyen,
    • Matthew Ruffalo,
    • and Ziv Bar-Joseph
    Genome Res. May 2025 35: 1219-1233; Published in Advance February 18, 2025, doi:10.1101/gr.279631.124
    ...from different tissues.Several recent efforts have attempted to generate atlas-scale single-cell data. Examples include The Human BioMolecular Atlas Program (HuBMAP) (HuBMAP Consortium 2019; Jain et al. 2023), the Human Cell Atlas (HCA) (Rozenblatt-Rosen et al. 2017), the Cellular Senescence Network...
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  5. Resource: Integrated single-cell multiome analysis reveals muscle fiber-type gene regulatory circuitry modulated by endurance exercise
    • Aliza B. Rubenstein,
    • Gregory R. Smith,
    • Zidong Zhang,
    • Xi Chen,
    • Toby L. Chambers,
    • Frederique Ruf-Zamojski,
    • Natalia Mendelev,
    • Wan Sze Cheng,
    • Michel Zamojski,
    • Mary Anne S. Amper,
    • Venugopalan D. Nair,
    • Andrew R. Marderstein,
    • Stephen B. Montgomery,
    • Olga G. Troyanskaya,
    • Elena Zaslavsky,
    • Todd Trappe,
    • Scott Trappe,
    • and Stuart C. Sealfon
    Genome Res. July 2025 35: 1664-1677; Published in Advance May 20, 2025, doi:10.1101/gr.280051.124
    ...)-expressing fibro-adipogenic progenitor cells. Single-cell regulatory circuit triad reconstruction (transcription factor, chromatin interaction site, regulated gene) also identifies largely distinct gene regulatory circuits modulated by exercise in the three muscle fiber types and LUM-expressing fibro...
  6. Method: Harnessing agent-based frameworks in CellAgentChat to unravel cell–cell interactions from single-cell and spatial transcriptomics
    • Vishvak Raghavan,
    • Yumin Zheng,
    • Yue Li,
    • and Jun Ding
    Genome Res. July 2025 35: 1646-1663; Published in Advance May 2, 2025, doi:10.1101/gr.279771.124
    ...(Fig. 2A, top). Notably, CellAgentChat showed significantly better results than CellPhoneDB, NICHES, SingleCellSignalR, NATMI, and scSeqComm, further underscoring its consistency and accuracy in inferring communication networks (Fig. 2A, top). On examining individual data sets, Cell...
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  7. Method: Inferring disease progression stages in single-cell transcriptomics using a weakly supervised deep learning approach
    • Fabien Wehbe,
    • Levi Adams,
    • Jordan Babadoudou,
    • Samantha Yuen,
    • Yoon-Seong Kim,
    • and Yoshiaki Tanaka
    Genome Res. January 2025 35: 135-146; Published in Advance December 2, 2024, doi:10.1101/gr.278812.123
    ...-associated molecular features.Over the past few years, single-cell technologies have rapidly advanced and been applied to patient-derived tissues to better understand and counter a variety of diseases (BRAIN Initiative Cell Census Network (BICCN) 2021). Comparative analysis with healthy donors’ data is widely...
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  8. Research: Integrating short-read and long-read single-cell RNA sequencing for comprehensive transcriptome profiling in mouse retina
    • Meng Wang,
    • Yumei Li,
    • Jun Wang,
    • Soo Hwan Oh,
    • Yexuan Cao,
    • and Rui Chen
    Genome Res. April 2025 35: 740-754; Published in Advance March 6, 2025, doi:10.1101/gr.279167.124
    ...a systematic comparison between single-cell long-read and conventional short-read RNA sequencing techniques. The transcriptome of approximately 30,000 mouse retina cells was profiled using 1.54 billion Illumina short reads and 1.40 billion Oxford Nanopore Technologies long reads. Consequently, we identify 44...
  9. Review: Advancements in prospective single-cell lineage barcoding and their applications in research
    • Xiaoli Zhang,
    • Yirui Huang,
    • Yajing Yang,
    • Qi-En Wang,
    • and Lang Li
    Genome Res. December 2024 34: 2147-2162; Published in Advance November 21, 2024, doi:10.1101/gr.278944.124
    ...; Rodriguez-Fraticelli et al. 2018). Additionally, in the “TracerSeq” study (Wagner et al. 2018), it was employed in the reconstruction of single-cell lineage histories in zebrafish, leveraging gene expression landscapes. Recently, episomes were used for cell transfection and genomic integration...
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  10. Review: Understanding isoform expression by pairing long-read sequencing with single-cell and spatial transcriptomics
    • Natan Belchikov,
    • Justine Hsu,
    • Xiang Jennie Li,
    • Julien Jarroux,
    • Wen Hu,
    • Anoushka Joglekar,
    • and Hagen U. Tilgner
    Genome Res. November 2024 34: 1735-1746; doi:10.1101/gr.279640.124
    ...the diversity of cell types using single-cell methods. The Human Cell Atlas project focuses on cataloging all human cells, while more specialized efforts exist in neuroscience, including both the PsychENCODE Project and the BRAIN Initiative's Cell Census Network (BICCN) and Cell Atlas Network (BICAN) (Bhaduri...
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