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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
..., Canberra 2601, Australia; 3Bioinformatics and Cellular Genomics, St Vincent’s Institute, Fitzroy, Victoria 3065, Australia ↵4 These authors contributed equally to this work. Corresponding author: kimanh.lecao@unimelb.edu.auAbstractGene networks provide a fundamental framework for understanding...
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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
...of Mariculture Breeding, Xiamen University, Xiamen, Fujian 361000, China; 4Xiamen Key Laboratory of Big Data Intelligent Analysis and Decision, Xiamen, Fujian 361005, China Corresponding author: wangying@xmu.edu.cnAbstractUnderstanding gene regulatory networks (GRNs) is crucial for deciphering cellular...
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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
...–specific TFs in regulating key genes associated with AD progression, linking transcriptional changes to genetic risk loci and highlighting potential mechanisms underlying disease pathology.View larger version: In this window In a new window Figure 5. Cell type–specific TF regulatory network. (A) TF regulatory...
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Resource: Single-nucleus multiomic profiling of the aging mouse substantia nigra reveals conserved gene alterations linked to Parkinson's disease
- Kangli Wang,
- Weikun Xia,
- Yingli Gu,
- Songpeng Zu,
- Qian Yang,
- Maria Luisa Amaral,
- Yaozhi Wang,
- Allen Wang,
- Xiang-Dong Fu,
- William C. Mobley,
- and Bing Ren
Genome Res. April 2026 36: 849-864; Published in Advance March 4, 2026, doi:10.1101/gr.281113.125
...are downregulated at early aging stages in oligodendrocyte. Our multiomic atlas underscores the substantial regulatory network changes during aging that may predispose to PD, providing valuable insights for furthering understanding of PD pathogenesis and potential therapeutic targets.Parkinson's disease (PD...
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Method: Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networks
- Prashanthi Ravichandran,
- Princy Parsana,
- Rebecca Keener,
- Kasper D. Hansen,
- and Alexis Battle
Genome Res. September 2025 35: 2087-2103; Published in Advance July 17, 2025, doi:10.1101/gr.280808.125
...in the data, we inferred two broad types of networks: consensus and tissue context-specific (context-specific). Our universal consensus network included all samples, regardless of tissue or disease. Our noncancer consensus network included healthy samples and samples with disease status other than cancer...
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Method: Bayesian inference of sample-specific coexpression networks
- Enakshi Saha,
- Viola Fanfani,
- Panagiotis Mandros,
- Marouen Ben Guebila,
- Jonas Fischer,
- Katherine H. Shutta,
- Dawn L. DeMeo,
- Camila M. Lopes-Ramos,
- and John Quackenbush
Genome Res. September 2024 34: 1397-1410; Published in Advance August 12, 2024, doi:10.1101/gr.279117.124
...in the drivers of biological processes.The majority of human traits and diseases are driven not by individual genes, but by networks of genes and proteins interacting with each other. Understanding how genes interact and cooperate under different conditions is a central challenge in deciphering the complexities...
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Method: Spatial Cellular Networks from omics data with SpaCeNet
- Stefan Schrod,
- Niklas Lück,
- Robert Lohmayer,
- Stefan Solbrig,
- Dennis Völkl,
- Tina Wipfler,
- Katherine H. Shutta,
- Marouen Ben Guebila,
- Andreas Schäfer,
- Tim Beißbarth,
- Helena U. Zacharias,
- Peter J. Oefner,
- John Quackenbush,
- and Michael Altenbuchinger
Genome Res. September 2024 34: 1371-1383; Published in Advance September 4, 2024, doi:10.1101/gr.279125.124
..., Massachusetts 02115, USA; 5Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA; 6Campus Institute Data Science (CIDAS), University of Göttingen, 37077 Göttingen, Germany; 7Peter L. Reichertz Institute for Medical Informatics of TU...
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Method: Diffusion-based generation of gene regulatory networks from scRNA-seq data with DigNet
- Chuanyuan Wang and
- Zhi-Ping Liu
Genome Res. February 2025 35: 340-354; Published in Advance December 18, 2024, doi:10.1101/gr.279551.124
...progression when cellular processes become dysregulated. Specifically, by applying DigNet, we meticulously compare the regulatory networks of T cells between normal and cancerous breast tissue samples, pinpointing crucial nodes that underlie the regulatory discrepancies driving disease progression...
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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
...as a multislice joint analysis framework featuring a precorrection mechanism that enables the precise identification of complex spatial domains, advancing disease pathology insights. STMSC assumes that precise three-dimensional (3D) reconstruction is essential for an in-depth investigation of tissue components...
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Method: Systematic identification of interchromosomal interaction networks supports the existence of specialized RNA factories
- Borislav Hrisimirov Hristov,
- William Stafford Noble,
- and Alessandro Bertero
Genome Res. October 2024 34: 1610-1623; Published in Advance September 25, 2024, doi:10.1101/gr.278327.123
...that jointly interact in trans. This method, trans-C, initiates probabilistic random walks with restarts from a set of seed loci to traverse an input Hi-C contact network, thereby identifying sets of trans-contacting loci. We validate trans-C in three increasingly complex models of established trans contacts...

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