Searching journal content for articles similar to Hoon et al. 13 (8): 1904.

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Method: spRefine denoises and imputes spatial transcriptomics with a reference-free framework powered by genomic language model
- Tianyu Liu,
- Tinglin Huang,
- Wengong Jin,
- Tinyi Chu,
- Rex Ying,
- and Hongyu Zhao
Genome Res. February 3, 2026 gr.281001.125; Published in Advance February 3, 2026, doi:10.1101/gr.281001.125
...spRefine denoises and imputes spatial1 transcriptomics with a reference-free framework2 powered by genomic language model3 Tianyu Liu1,2, Tinglin Huang3, Wengong Jin4,5, Tinyi Chu2, Rex4 Ying3, Hongyu Zhao1,2*5 1Interdepartmental Program in Computational Biology &6 Bioinformatics, Yale University...
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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...
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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...
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Method: A novel multislice framework for precision 3D spatial domain reconstruction and disease pathology analysis
- Daijun Zhang,
- Ren Qi,
- Xun Lan,
- and Bin Liu
Genome Res. August 2025 35: 1794-1808; Published in Advance July 14, 2025, doi:10.1101/gr.280281.124
...that different methods may be better suited to different analytical goals; for example, if precise cell type deconvolution is the primary objective, purpose-built methods such as Cell2Location may be preferable. Importantly, as detailed in the Methods section “Flexibility of the framework,” STMSC is designed...
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Method: Exon Nomenclature And Classification of Transcripts (ENACT) provides a systematic framework to annotate exon attributes
- Paras Verma,
- Deeksha Thakur,
- Deepanshi Awasthi,
- and Shashi Bhushan Pandit
Genome Res. June 2025 35: 1440-1455; Published in Advance May 7, 2025, doi:10.1101/gr.279878.124
...remains limited owing to dearth of subsequent proteogenomic consequences. To coalesce the genomic information embedded in exons with isoform sequences, we present an innovative framework, “Exon Nomenclature And Classification of Transcripts” (ENACT). This centralizes exonic loci such that protein sequence...
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Method: Matrix sketching framework for linear mixed models in association studies
- Myson Burch,
- Aritra Bose,
- Gregory Dexter,
- Laxmi Parida,
- and Petros Drineas
Genome Res. September 2024 34: 1304-1311; Published in Advance September 4, 2024, doi:10.1101/gr.279230.124
...sketching to develop a fast and efficient LMM method called Matrix-Sketching LMM (MaSk-LMM) by sketching the genotype matrix to reduce its dimensions and speed up computations. Our framework comes with both theoretical guarantees and a strong empirical performance compared to the current state...
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Method: Genetics-driven risk predictions leveraging the Mendelian randomization framework
- Daniel Sens,
- Liubov Shilova,
- Ludwig Gräf,
- Maria Grebenshchikova,
- Bjoern M. Eskofier,
- and Francesco Paolo Casale
Genome Res. September 2024 34: 1276-1285; Published in Advance September 27, 2024, doi:10.1101/gr.279252.124
...relationships between risk factors. Although extensions to more complex parametric forms or flexible neural network functions would mitigate this, managing overfitting will represent a key challenge. Future work to address this may involve extending PRiMeR's Bayesian framework by integrating recent developments...
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Method: Geometric deep learning framework for de novo genome assembly
- Lovro Vrček,
- Xavier Bresson,
- Thomas Laurent,
- Martin Schmitz,
- Kenji Kawaguchi,
- and Mile Šikić
Genome Res. April 2025 35: 839-849; Published in Advance October 29, 2024, doi:10.1101/gr.279307.124
...Geometric deep learning framework for de novo assembly Lovro Vrček1,2, Xavier Bresson3, Thomas Laurent4, Martin Schmitz1,3, Kenji Kawaguchi3 and Mile Šikić1,2 1Genome Institute of Singapore, A*STAR, Singapore 138672; 2Faculty of Electrical Engineering and Computing, University of Zagreb, 10000...
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Method: A fast and adaptive detection framework for genome-wide chromatin loop mapping from Hi-C data
- Siyuan Chen,
- Jiuming Wang,
- Inkyung Jung,
- Zhaowen Qiu,
- Xin Gao,
- and Yu Li
Genome Res. August 2024 34: 1174-1184; Published in Advance August 13, 2024, doi:10.1101/gr.279274.124
...A fast and adaptive detection framework for -wide chromatin loop mapping from Hi-C data Siyuan Chen1,2,3,8, Jiuming Wang4,8, Inkyung Jung5, Zhaowen Qiu6, Xin Gao1,2,3 and Yu Li4,7 1Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King...
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Method: Theoretical framework for the difference of two negative binomial distributions and its application in comparative analysis of sequencing data
- Alicia Petrany,
- Ruoyu Chen,
- Shaoqiang Zhang,
- and Yong Chen
Genome Res. October 2024 34: 1636-1650; Published in Advance October 15, 2024, doi:10.1101/gr.278843.123
...data.With this general framework established, we can apply DOTNB to various HTS data types for the comparative analysis of two independent data sets. Typical examples include but are not limited to DEG analysis for scRNA-seq. In this application, the expression counts of each gene in two data sets...
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