Searching journal content for articles similar to Greenbaum et al. 29 (12): 2020.

Displaying results 1-10 of 40
For checked items
  1. Method: Debiased personalized gene coexpression networks for population-scale scRNA-seq data
    • Shan Lu and
    • Sunduz Keles
    Genome Res. June 9, 2023 gr.277363.122; Published in Advance June 9, 2023, doi:10.1101/gr.277363.122
    ...networks, yields more accurate estimates of network centrality measures and modules, and improves the faithfulness of networks estimated from separate batches of the datasets. We showcase unique analyses enabled by Dozer in two population-scale scRNAseq applications. Coexpression network-based centrality...
    ACCEPTED MANUSCRIPT
  2. Method: Fast and flexible bacterial genomic epidemiology with PopPUNK
    • John A. Lees,
    • Simon R. Harris,
    • Gerry Tonkin-Hill,
    • Rebecca A. Gladstone,
    • Stephanie W. Lo,
    • Jeffrey N. Weiser,
    • Jukka Corander,
    • Stephen D. Bentley,
    • and Nicholas J. Croucher
    Genome Res. February 2019 29: 304-316; Published in Advance January 24, 2019, doi:10.1101/gr.241455.118
    ...not fully exploit core and accessory genomic variation, and they cannot both automatically identify, and subsequently expand, clusters of significantly similar isolates in large data sets spanning entire species. Here, we describe PopPUNK (Population Partitioning Using Nucleotide K-mers), a software...
    OPEN ACCESS ARTICLE
  3. Research: Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver
    • Xia Yang,
    • Bin Zhang,
    • Cliona Molony,
    • Eugene Chudin,
    • Ke Hao,
    • Jun Zhu,
    • Andrea Gaedigk,
    • Christine Suver,
    • Hua Zhong,
    • J. Steven Leeder,
    • F. Peter Guengerich,
    • Stephen C. Strom,
    • Erin Schuetz,
    • Thomas H. Rushmore,
    • Roger G. Ulrich,
    • J. Greg Slatter,
    • Eric E. Schadt,
    • Andrew Kasarskis,
    • and Pek Yee Lum
    Genome Res. August 2010 20: 1020-1036; Published in Advance June 10, 2010, doi:10.1101/gr.103341.109
    ...of drugs, fatty acids, amino acids, and steroids. Genome-wide association analyses between genetic polymorphisms and P450 expression or enzyme activities revealed sets of SNPs associated with P450 traits, and suggested the existence of both cis -regulation of P450 expression (especially for CYP2D6...
    OPEN ACCESS ARTICLE
  4. 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. March 5, 2026 ; Published in Advance March 5, 2026, doi:10.1101/gr.281171.125
    ...ETAS, coexpression-based TF activity scores). Data and setting We analyzed two data sets. The first was the PBMC3Kdata set from 10xGenomics, often used as a benchmark. The second data setwas a Perturb-seq experiment (Papalexi et al. 2021), in which the THP1 monocyte cell line was subjected to pooled CRISPR screening...
    OPEN ACCESS ARTICLE
  5. Research: Mapping multitissue regulatory variants reveals a liver-centric coexpression network associated with duck egg-laying performance
    • Yang Xi,
    • Jingjing Qi,
    • Zhao Yang,
    • Yutian Zeng,
    • Huicong Zhang,
    • Qiuyu Tao,
    • Mengru Xu,
    • Anqi Huang,
    • Shenqiang Hu,
    • Chunchun Han,
    • Lili Bai,
    • Jiwei Hu,
    • Jiwen Wang,
    • Liang Li,
    • Lingzhao Fang,
    • and Hehe Liu
    Genome Res. October 2025 35: 2211-2225; Published in Advance September 10, 2025, doi:10.1101/gr.280345.124
    ..., several modules were significantly correlated with modules in the liver (ME1, ME3, ME5). In contrast, no significant cross-tissue correlations were observed among the ovary, spleen, and shell gland themselves (Fig. 6A). We employed a Bayesian network-based approach to explore the potential causal...
  6. 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
    ...-specific covariance Vi. On the other hand, if the ith sample is an outlier with respect to the rest of the population, we recommend using a large value of δi, thereby decreasing estimation bias. Alternatively, we can set δi = δ, to some arbitrary value between (0, 1). In the following section, we describe...
    OPEN ACCESS ARTICLE
  7. 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
    ...and differences between network architectures of the noncancer consensus and cancer consensus networks based on shared and distinct hub genes, because central genes are likely to be more relevant to network functionality (Pastor-Satorras et al. 2003), and the identification of hubs has led to the discovery...
    OPEN ACCESS ARTICLE
  8. Method: A gene regulatory network–aware graph learning method for cell identity annotation in single-cell RNA-seq data
    • Mengyuan Zhao,
    • Jiawei Li,
    • Xiaoyi Liu,
    • Ke Ma,
    • Jijun Tang,
    • and Fei Guo
    Genome Res. July 2024 34: 1036-1051; Published in Advance August 12, 2024, doi:10.1101/gr.278439.123
    ...) enrichment.scHGR improves accuracy of cell annotations on intra–data setsTo assess the performance of scHGR, we compare it to a variety of cell annotation tools, including a decision-tree (DT)-based method (scHPL) (Michielsen et al. 2021), a neural network-based method (ACTINN) (Ma and Pellegrini 2020...
  9. Method: Dynamic regulatory module networks for inference of cell type–specific transcriptional networks
    • Alireza Fotuhi Siahpirani,
    • Sara Knaack,
    • Deborah Chasman,
    • Morten Seirup,
    • Rupa Sridharan,
    • Ron Stewart,
    • James Thomson,
    • and Sushmita Roy
    Genome Res. July 2022 32: 1367-1384; Published in Advance June 15, 2022, doi:10.1101/gr.276542.121
    ..., and uses multitask learning to capture network dynamics across linearly and hierarchically related contexts. We applied DRMNs to study regulatory network dynamics in three developmental processes, each showing different temporal relationships and measuring a different combination of regulatory genomic data...
    OPEN ACCESS ARTICLE
  10. Research: A systems genetics approach reveals environment-dependent associations between SNPs, protein coexpression, and drought-related traits in maize
    • Mélisande Blein-Nicolas,
    • Sandra Sylvia Negro,
    • Thierry Balliau,
    • Claude Welcker,
    • Llorenç Cabrera-Bosquet,
    • Stéphane Dimitri Nicolas,
    • Alain Charcosset,
    • and Michel Zivy
    Genome Res. November 2020 30: 1593-1604; Published in Advance October 15, 2020, doi:10.1101/gr.255224.119
    ...Montpellier, SupAgro, F34060 Montpellier, France Corresponding authors: michel.zivy@inra.fr, melisande.blein-nicolas@inra.frAbstractThe effect of drought on maize yield is of particular concern in the context of climate change and human population growth. However, the complexity of drought-response mechanisms...
For checked items

Search Results

Next 10 » New Search

Modify Results

Citation format:
Results / page:
Results order:

This search

  • Alert me when new articles matching this search are published
  • Download all citations on this page to my citation manager

Preprint Server



Current Issue

  1. March 2026, 36 (3)
  1. Current Issue
  1. Alert me to new issues of Genome Research