Searching journal content for articles similar to Belokopytova et al. 30 (1): 72.

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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
...and optimizing the hyperparameters. We demonstrate how gene-related biometrics influence target traits and how accounting for interaction effects enhances prediction accuracy. In addition, we apply Shapley additive explanations (SHAP) to quantify the SNP additive and epistatic effects. To bridge the gap between...
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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
...-Net, an interpretable geometric deep learning–based framework that effectively models the nonlinearity of biological systems for enhanced disease prediction and biological discovery. PRS-Net begins by deconvoluting the -wide PRS at the single-gene resolution and then explicitly encapsulates gene–gene interactions...
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Mini-Review: Revisiting models of enhancer–promoter communication in gene regulation
- Gilad Barshad and
- Charles G. Danko
Genome Res. June 2025 35: 1277-1286; doi:10.1101/gr.278389.123
...extrusion, which exerts indirect effects on transcriptional hubs or loops.Distances between enhancer–promoter DNA during interactionsA key difference between the structural bridge and hub models concerns the distance between enhancer and promoter DNA. The structural bridge model predicts that the enhancer...
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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
...). The predicted signals and peaks co-localized with many known promoters and enhancers (Moore et al. 2020), corroborating quantitative overlap analyses with ground-truth accessible regions and confirming the high fidelity of predicted peak shapes (Fig. 2E–H). Notably, some enhancers were uniquely identified...
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Research: Genetic effects on chromatin accessibility uncover mechanisms of liver gene regulation and quantitative traits
- Kevin W. Currin,
- Hannah J. Perrin,
- Gautam K. Pandey,
- Abdalla A. Alkhawaja,
- Swarooparani Vadlamudi,
- Annie E. Musser,
- Amy S. Etheridge,
- K. Alaine Broadaway,
- Jonathan D. Rosen,
- Arushi Varshney,
- Amarjit S. Chaudhry,
- Paul J. Gallins,
- Fred A. Wright,
- Yi-hui Zhou,
- Stephen C.J. Parker,
- Laura M. Raffield,
- Erin G. Schuetz,
- Federico Innocenti,
- and Karen L. Mohlke
Genome Res. July 2025 35: 1485-1502; Published in Advance May 20, 2025, doi:10.1101/gr.279741.124
...QTL for TENM2, we validated regulatory activity for a variant within a predicted driver element that is coordinately regulated with 39 other elements. At another locus, we validate a predicted enhancer of RALGPS2 using CRISPR interference and demonstrate allelic effects on transcription for a haplotype within...
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Research: Analyzing super-enhancer temporal dynamics reveals potential critical enhancers and their gene regulatory networks underlying skeletal muscle development
- Song Zhang,
- Chao Wang,
- Shenghua Qin,
- Choulin Chen,
- Yongzhou Bao,
- Yuanyuan Zhang,
- Lingna Xu,
- Qingyou Liu,
- Yunxiang Zhao,
- Kui Li,
- Zhonglin Tang,
- and Yuwen Liu
Genome Res. December 2024 34: 2190-2202; Published in Advance October 21, 2024, doi:10.1101/gr.278344.123
...-regulatory interactions based on PSM topologically associating domains (TADs), retaining only interactions where the candidate critical enhancer and its potential target gene were within the same TAD (Zhao et al. 2021). The final network consisted of 30 candidate critical enhancers (20, 7, and 3 from Con, DN, and TS SEs...
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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
...agent rule modifications, facilitating the development of novel intervention strategies. This ABM method unlocks an in-depth understanding of cellular signaling interactions across various biological contexts, thereby enhancing in silico studies for cellular communication–based therapies...
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Method: Power-law behavior of transcriptional bursting regulated by enhancer–promoter communication
- Zihao Wang,
- Zhenquan Zhang,
- Songhao Luo,
- Tianshou Zhou,
- and Jiajun Zhang
Genome Res. January 2024 34: 106-118; Published in Advance January 3, 2024, doi:10.1101/gr.278631.123
...bursting. The theory predicts that power law can be a general rule to quantitatively describe bursting modulations by E-P spatial communication. Specifically, burst frequency and burst size are up-regulated by E-P communication strength, following power laws with positive exponents. Analysis of the scaling...
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Research: Enhancer–silencer transitions in the human genome
- Di Huang and
- Ivan Ovcharenko
Genome Res. March 2022 32: 437-448; Published in Advance February 1, 2022, doi:10.1101/gr.275992.121
...learning models in the prediction of chromatin states, TF binding occupancies, and enhancers (Alipanahi et al. 2015; Zhou and Troyanskaya 2015; Thibodeau et al. 2018), as well as our prior work on silencer detection (Huang et al. 2019), we trained a sequence-based deep learning model to identify silencers...
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Method: Privacy-preserving biological age prediction over federated human methylation data using fully homomorphic encryption
- Meir Goldenberg,
- Loay Mualem,
- Amit Shahar,
- Sagi Snir,
- and Adi Akavia
Genome Res. September 2024 34: 1324-1333; Published in Advance September 5, 2024, doi:10.1101/gr.279071.124
.... This strengthening requires only a single round of interaction between the servers, transmitting a single ciphertext in each direction. Moreover, if we slightly relax the output hiding requirement as to allow exposing the common denominator of the produced e-ages, then this privacy enhancement incurs no interaction...
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