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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
..., and interpretable exploration of causal GRNs with prior knowledge and multi-omics data.Gene regulatory networks (GRNs), which encapsulate the complex interactions among transcription factors (TFs), target genes, and various regulatory elements, constitute the core machinery of gene regulation (Levine and Davidson...
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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
.... 2022). However, rigorous statistical models to infer complex cellular interdependencies from spatially distributed molecular data are still missing.The statistical inference of correlation-based molecular networks from high-dimensional omics data is based on the assumption that coordinated expression...
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LETTER: An Arabidopsis gene network based on the graphical Gaussian model
- Shisong Ma,
- Qingqiu Gong,
- and Hans J. Bohnert
Genome Res. November 2007 17: 1614-1625; Published in Advance October 5, 2007, doi:10.1101/gr.6911207
...as subnetworks and added novel components to known edges. Finally, the network reconciled individual subnetworks in a topology joined at the whole-genome level and provided a general framework that can instruct future studies on plant metabolism and stress responses. The network model is included. Footnotes...
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Research: Dynamic metabolic and molecular changes during seasonal shrinking in Sorex araneus
- William R. Thomas,
- Cecilia Baldoni,
- Yuanyuan Zeng,
- David Carlson,
- Julie Holm-Jacobsen,
- Marion Muturi,
- Dominik von Elverfeldt,
- Tue B. Bennike,
- Dina K.N. Dechmann,
- John Nieland,
- Angelique P. Corthals,
- and Liliana M. Dávalos
Genome Res. January 2026 36: 61-70; Published in Advance November 4, 2025, doi:10.1101/gr.280639.125
...To understand how gene expression in the liver changes across seasonal stages, and whether these shifts align with the body size changes of Dehnel's phenomenon, we began by examining the global transcriptomic patterns (Supplemental Data S4). Exploratory analyses of liver gene expression revealed patterns...
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Perspective: Advances in spatial transcriptomic data analysis
- Ruben Dries,
- Jiaji Chen,
- Natalie del Rossi,
- Mohammed Muzamil Khan,
- Adriana Sistig,
- and Guo-Cheng Yuan
Genome Res. October 2021 31: 1706-1718; doi:10.1101/gr.275224.121
..., Stegle O. 2018. Multi-omics factor analysis: a framework for unsupervised integration of multi-omics data sets. Mol Syst Biol 14: e8124. doi:10.15252/msb.20178124 ↵Armingol E, Officer A, Harismendy O, Lewis NE. 2021. Deciphering cell–cell interactions and communication from gene expression. Nat Rev Genet...
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Method: Efficient computation of Faith's phylogenetic diversity with applications in characterizing microbiomes
- George Armstrong,
- Kalen Cantrell,
- Shi Huang,
- Daniel McDonald,
- Niina Haiminen,
- Anna Paola Carrieri,
- Qiyun Zhu,
- Antonio Gonzalez,
- Imran McGrath,
- Kristen L. Beck,
- Daniel Hakim,
- Aki S. Havulinna,
- Guillaume Méric,
- Teemu Niiranen,
- Leo Lahti,
- Veikko Salomaa,
- Mohit Jain,
- Michael Inouye,
- Austin D. Swafford,
- Ho-Cheol Kim,
- Laxmi Parida,
- Yoshiki Vázquez-Baeza,
- and Rob Knight
Genome Res. November 2021 31: 2131-2137; Published in Advance September 3, 2021, doi:10.1101/gr.275777.121
..., Estaki M, Haiminen N, et al. 2021. EMPress enables tree-guided, interactive, and exploratory analyses of multi-omic data sets. mSystems 6: e01216-20. doi:10.1128/mSystems.01216-20 ↵Cordova J, Navarro G. 2016. Simple and efficient fully-functional succinct trees. Theor 656: 135–145. doi:10.1016/j.tcs.2016...
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Method: A Bayesian inference transcription factor activity model for the analysis of single-cell transcriptomes
- Shang Gao,
- Yang Dai,
- and Jalees Rehman
Genome Res. July 2021 31: 1296-1311; Published in Advance June 30, 2021, doi:10.1101/gr.265595.120
...to study cellular heterogeneity. One of the challenges in scRNA-seq data analysis is integrating different types of biological data to consistently recognize discrete biological functions and regulatory mechanisms of cells, such as transcription factor activities and gene regulatory networks in distinct...
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