Searching journal content for articles similar to Fu et al. 34 (9): 1294.

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  1. Method: Automated interpretable artificial intelligence genomic prediction with AIGP
    • Lei Wei,
    • Ziqin Jiang,
    • Baoliang Fan,
    • Yidan Yan,
    • Zhenqiang Xu,
    • Xiaoxiang Hu,
    • and Yuzhe Wang
    Genome Res. April 2026 36: 814-826; Published in Advance March 5, 2026, doi:10.1101/gr.281006.125
    ...prediction; however, it often struggles with interpretability because of its black-box nature. Here, we evaluate 12 ML models alongside GBLUP and BayesR to identify key factors influencing genomic prediction performance across traits with different genetic architectures in multiple agricultural species...
  2. Method: Kernel-bounded clustering for spatial transcriptomics enables scalable discovery of complex spatial domains
    • Hang Zhang,
    • Yi Zhang,
    • Kai Ming Ting,
    • Jie Zhang,
    • and Qiuran Zhao
    Genome Res. February 2025 35: 355-367; Published in Advance February 5, 2025, doi:10.1101/gr.278983.124
    ...space on which clustering is performed), and they have high computational complexity, resulting in unsatisfactory clustering outcomes and slow execution time even with GPUs. Rather than focusing on data transformation techniques, we propose a new clustering algorithm called kernel-bounded clustering...
    OPEN ACCESS ARTICLE
  3. Method: Interpretable phenotype decoding from multicondition sequencing data with ALPINE
    • Wei-Hao Lee,
    • Lechuan Li,
    • Ruth Dannenfelser,
    • and Vicky Yao
    Genome Res. December 2025 35: 2756-2769; Published in Advance October 22, 2025, doi:10.1101/gr.280566.125
    ...and finding condition-associated effects on genes, cells, and intercondition interactions. Compared to existing disentanglement methods, ALPINE provides significant advantages in integration performance, interpretability, and scalability.Across both simulations and real data sets, our analyses reveal...
  4. Method: A scalable computational framework for predicting gene expression from candidate cis-regulatory elements
    • Qinhu Zhang,
    • Siguo Wang,
    • Zhipeng Li,
    • Wenzheng Bao,
    • Wenjian Liu,
    • and De-Shuang Huang
    Genome Res. February 2026 36: 361-374; Published in Advance January 16, 2026, doi:10.1101/gr.281219.125
    ...@eitech.edu.cnAbstractDeciphering the relationships between cis-regulatory elements (CREs) and target gene expression has been a long-standing unsolved problem in molecular biology, and the dynamics of CREs in different cell types make this problem more challenging. To address this challenge, we propose a scalable computational framework...
    OPEN ACCESS ARTICLE
  5. Method: Pangenome-spanning epistasis and coselection analysis via de Bruijn graphs
    • Juri Kuronen,
    • Samuel T. Horsfield,
    • Anna K. Pöntinen,
    • Sudaraka Mallawaarachchi,
    • Sergio Arredondo-Alonso,
    • Harry Thorpe,
    • Rebecca A. Gladstone,
    • Rob J.L. Willems,
    • Stephen D. Bentley,
    • Nicholas J. Croucher,
    • Johan Pensar,
    • John A. Lees,
    • Gerry Tonkin-Hill,
    • and Jukka Corander
    Genome Res. July 2024 34: 1081-1088; Published in Advance August 12, 2024, doi:10.1101/gr.278485.123
    ...adaptation and evolution are hampered by the difficulty of measuring traits such as virulence, drug resistance, and transmissibility in large populations. In contrast, it is now feasible to obtain high-quality complete assemblies of many bacterial s thanks to scalable high-accuracy long-read sequencing...
    OPEN ACCESS ARTICLE
  6. Method: EnDeep4mC predicts DNA N4-methylcytosine sites using a dual-adaptive feature encoding framework in deep ensembles
    • Shuyu Zhang,
    • Quan Zou,
    • Mengting Niu,
    • Zhibin Lv,
    • Antony Stalin,
    • and Ximei Luo
    Genome Res. March 2026 36: 589-599; Published in Advance February 17, 2026, doi:10.1101/gr.280977.125
    ..., requires efficient computational detection methods due to experimental limitations. Although machine learning predictors have been proposed, their performance could be enhanced through systematic optimization of feature encoding schemes. Here, we propose EnDeep4mC, a dual-adaptive framework integrating...
    OPEN ACCESS ARTICLE
  7. Method: Scalable cell-specific coexpression networks for granular regulatory pattern discovery with NeighbourNet
    • Yidi Deng,
    • Jiadong Mao,
    • Jarny Choi,
    • and Kim-Anh Lê Cao
    Genome Res. April 2026 36: 785-801; Published in Advance March 5, 2026, doi:10.1101/gr.281171.125
    ...simplified meta-TF–target networks with improved interpretability. (D3) We adapted the NicheNet framework to integrate gene regulation and signaling interaction databases from OmniPath, constructing integrated prior knowledge networks (PKNs). Annotating CSNs with these PKNs transforms them...
    OPEN ACCESS ARTICLE
  8. Method: Partitioned multi-MUM finding for scalable pangenomics with MumemtoM
    • Vikram S. Shivakumar and
    • Ben Langmead
    Genome Res. February 2026 36: 397-404; Published in Advance November 7, 2025, doi:10.1101/gr.280940.125
    ...Vikram S. Shivakumar and Ben Langmead Department of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, USA Corresponding authors: vshivak1@jhu.edu, langmea@cs.jhu.eduAbstractPan collections are growing to hundreds of high-quality s. This necessitates scalable methods...
  9. Method: Scalable summary-statistics-based heritability estimation method with individual genotype level accuracy
    • Moonseong Jeong,
    • Ali Pazokitoroudi,
    • Zhengtong Liu,
    • and Sriram Sankararaman
    Genome Res. September 2024 34: 1286-1293; Published in Advance July 22, 2024, doi:10.1101/gr.279207.124
    ...architecture underlying various diseases and traits. Methods that aim to estimate SNP heritability from individual genotype and phenotype data are limited by their ability to scale to Biobank-scale data sets and by the restrictions in access to individual-level data. These limitations have motivated...
    OPEN ACCESS ARTICLE
  10. Method: Enhancing nanopore adaptive sampling for PromethION using readfish at scale
    • Rory Munro,
    • Alexander Payne,
    • Nadine Holmes,
    • Chris Moore,
    • Inswasti Cahyani,
    • and Matthew Loose
    Genome Res. April 2025 35: 877-885; Published in Advance January 30, 2025, doi:10.1101/gr.279329.124
    ...variants in human diseases and other traits. Nat Genet 53: 779–786. doi:10.1038/s41588-021-00865-4 ↵Chen Z, Gustavsson EK, Macpherson H, Anderson C, Clarkson C, Rocca C, Self E, Alvarez Jerez P, Scardamaglia A, Pellerin D, et al. 2024. Adaptive long-read sequencing reveals GGC repeat expansion in ZFHX3...
    OPEN ACCESS ARTICLE
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