Searching journal content for articles similar to Nelander et al. 13 (8): 1838.

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  1. Resource: Cell type–specific gene regulatory atlas prioritizes drug targets and repurposable medicines in Alzheimer's disease
    • Yunxiao Ren,
    • Ming Hu,
    • Yang E. Li,
    • Andrew A. Pieper,
    • Jeffrey Cummings,
    • and Feixiong Cheng
    Genome Res. March 2026 36: 645-659; Published in Advance January 21, 2026, doi:10.1101/gr.280436.125
    ...) Collection and preprocessing of snRNA-seq and snATAC-seq data sets in physical space. (B) Multiple analysis to identify an AD-associated gene list including differential gene expression analysis; identification of cCRE; cell type–specific, AD-associated risk variants; and peak-to-gene linkages. (C) Two...
    OPEN ACCESS ARTICLE
  2. Resource: Multitissue single-nucleus RNA-seq reveals cell type–specific regulatory patterns of alternative polyadenylation in pigs
    • Qiuhan Wen,
    • Zhen Wang,
    • Qi Bao,
    • Tianli Ding,
    • Haihan Zhang,
    • Jianbo Li,
    • Zhuang Liu,
    • Jieping Huang,
    • and Guoqiang Yi
    Genome Res. September 2025 35: 2116-2129; Published in Advance June 16, 2025, doi:10.1101/gr.280095.124
    ...binding sites and miRNA binding sites. Shortening of the 3′ UTR may result in the deletion of these sites, thereby enabling the gene to adopt cell type–specific functions. For example, during spermatogenesis, the 3′ UTR of the CD47 gene progressively shortens, resulting in the loss of predicted binding...
  3. Research: Functional genomics analysis of developing zebrafish and human endoderm reveals highly conserved cis-regulatory modules acting during vertebrate organogenesis
    • Daniela M. Riley,
    • Randa Elsayed,
    • Mark D. Walsh,
    • Simaran Johal,
    • Ying Lin,
    • Harry Walton,
    • Till Bretschneider,
    • Sascha Ott,
    • and Andrew C. Nelson
    Genome Res. March 4, 2026 ; Published in Advance March 4, 2026, doi:10.1101/gr.280838.125
    ...patterns indicative of alternative target genes, we analyzed subsets unique to each population as well as the complete combined set (Fig. 4D). Furthermore, because HCNEs are known to have nonrandom genomic distribution patterns with specific biases toward trans-dev genes, we testedwhether the 1701 HCNEs...
  4. Method: Infernape uncovers cell type–specific and spatially resolved alternative polyadenylation in the brain
    • Bowei Kang,
    • Yalan Yang,
    • Kaining Hu,
    • Xiangbin Ruan,
    • Yi-Lin Liu,
    • Pinky Lee,
    • Jasper Lee,
    • Jingshu Wang,
    • and Xiaochang Zhang
    Genome Res. October 2023 33: 1774-1787; Published in Advance October 31, 2023, doi:10.1101/gr.277864.123
    ...cell types with known marker genes (Fig. 3A; Supplemental Fig. S3C), and transferred cell-type labels from the scRNA-seq data set to the snRNA-seq data set (Supplemental Fig. S3C,D). Although the total number of high-quality cells is about twice in the snRNA-seq data than in the scRNA-seq data...
    OPEN ACCESS ARTICLE
  5. Method: Early feature extraction drives model performance in high-resolution chromatin accessibility prediction
    • Aayush Grover,
    • Till Muser,
    • Liine Kasak,
    • Lin Zhang,
    • Ekaterina Krymova,
    • and Valentina Boeva
    Genome Res. March 2026 36: 619-629; Published in Advance January 12, 2026, doi:10.1101/gr.281042.125
    ...for downstream tasks, including prediction of transcription factor binding (Cazares et al. 2023), cell type–specific chromatin structure (Tan et al. 2023; Yang et al. 2023; Zhang et al. 2023; Gao et al. 2024; Grover et al. 2024), and gene expression (Karbalayghareh et al. 2022; Zhang et al. 2023). Therefore...
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  6. Method: Highly accurate reference and method selection for universal cross–data set cell type annotation with CAMUS
    • Qunlun Shen,
    • Shuqin Zhang,
    • and Shihua Zhang
    Genome Res. November 2025 35: 2527-2538; Published in Advance October 1, 2025, doi:10.1101/gr.280821.125
    ...hundreds of genes. This limitation results in blurred cluster boundaries and difficulties in manual annotation (Shen et al. 2025). Therefore, most scST studies utilize scRNA-seq data sets as a reference to help annotate scST data sets. For example, scANVI was employed to annotate MERFISH data derived from...
  7. Method: Automated interpretable artificial intelligence genomic prediction with AlGP
    • Lei Wei,
    • Ziqin Jiang,
    • Baoliang Fan,
    • Yidan Yan,
    • Zhenqiang Xu,
    • Xiaoxiang Hu,
    • and Yuzhe Wang
    Genome Res. March 5, 2026 ; Published in Advance March 5, 2026, doi:10.1101/gr.281006.125
    ...dimension reduction, whereas the green background signifies the data set after dimension reduction. The PCA and PHATE results are represented on the left and right sides of the dotted line, respectively. Wei et al. 8 Genome Research www..org genomic era, which posits that each gene plays a synergistic role...
  8. Research: Systematic identification and characterization of exon–intron circRNAs
    • Yinchun Zhong,
    • Yan Yang,
    • Xiaolin Wang,
    • Bingbing Ren,
    • Xueren Wang,
    • Ge Shan,
    • and Liang Chen
    Genome Res. March 2024 34: 376-393; Published in Advance April 12, 2024, doi:10.1101/gr.278590.123
    ...RNAs, circRNAs, and EIciRNAs, as well as parental genes of EIciRNAs and all circRNAs, from available HTS data sets (PRJCA000751) of 17 human tissues. P-values were calculated using the Wilcoxon rank-sum test. (PCGs) Protein-coding genes. (G) GO analysis of parental genes of EIciRNAs. The most significant...
    OPEN ACCESS ARTICLE
  9. Method: Modeling gene interactions in polygenic prediction via geometric deep learning
    • Han Li,
    • Jianyang Zeng,
    • Michael P. Snyder,
    • and Sai Zhang
    Genome Res. January 2025 35: 178-187; Published in Advance November 19, 2024, doi:10.1101/gr.279694.124
    .... The results on the mixed ancestry test set were also reported. The bar plot and error bar denote the mean and standard error, respectively. The training, validation, and testing procedure was conducted for six repeats.PRS-Net identifies disease-relevant genes and GGIsFollowing the demonstration...
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  10. Method: Dynamic regulatory module networks for inference of cell type–specific transcriptional networks
    • Alireza Fotuhi Siahpirani,
    • Sara Knaack,
    • Deborah Chasman,
    • Morten Seirup,
    • Rupa Sridharan,
    • Ron Stewart,
    • James Thomson,
    • and Sushmita Roy
    Genome Res. July 2022 32: 1367-1384; Published in Advance June 15, 2022, doi:10.1101/gr.276542.121
    ...their relatedness, for example, by time or a lineage. DRMNs represent the cell type–specific regulatory network by a concise set of gene expression modules, defined by groups of genes with similar expression levels, and their associated regulatory programs (regulators predicted for that module and parameters...
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