Searching journal content for articles similar to Xiong et al. 11 (11): 1878.

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  1. Method: Cross-species cell-type assignment from single-cell RNA-seq data by a heterogeneous graph neural network
    • Xingyan Liu,
    • Qunlun Shen,
    • and Shihua Zhang
    Genome Res. January 2023 33: 96-111; Published in Advance December 16, 2022, doi:10.1101/gr.276868.122
    ...-type assignment is a crucial step to achieve that. However, the poorly annotated and limited known biomarkers hinder us from assigning cell identities for nonmodel species. Here, we design a heterogeneous graph neural network model, CAME, to learn aligned and interpretable cell and gene embeddings for cross...
  2. Resource: Precision environmental health monitoring by longitudinal exposome and multi-omics profiling
    • Peng Gao,
    • Xiaotao Shen,
    • Xinyue Zhang,
    • Chao Jiang,
    • Sai Zhang,
    • Xin Zhou,
    • Sophia Miryam Schüssler-Fiorenza Rose,
    • and Michael Snyder
    Genome Res. June 2022 32: 1199-1214; Published in Advance June 6, 2022, doi:10.1101/gr.276521.121
    ...personal exposome profiles across 18 time points and annotated 1265 genera, 158 known chemical stressors among 3299 chemical features, and 10 environmental factors, which included physical stressors that may impact environmental health in this study (Fig. 1B). These genera and known chemical stressors were...
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  3. Research: Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single-cell resolution
    • Justyna A. Resztak,
    • Julong Wei,
    • Samuele Zilioli,
    • Edward Sendler,
    • Adnan Alazizi,
    • Henriette E. Mair-Meijers,
    • Peijun Wu,
    • Xiaoquan Wen,
    • Richard B. Slatcher,
    • Xiang Zhou,
    • Francesca Luca,
    • and Roger Pique-Regi
    Genome Res. June 2023 33: 839-856; Published in Advance July 13, 2023, doi:10.1101/gr.276765.122
    ...to glucocorticoids in activated PBMCs from 96 African American youths with asthma and the genetic basis of variation in gene expression mean and variability across individuals.ResultsIdentification of major cell types and gene expression patternsTo systematically characterize genetic determinants of transcriptional...
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  4. METHODS: A Classification-Based Machine Learning Approach for the Analysis of Genome-Wide Expression Data
    • James Lyons-Weiler,
    • Satish Patel,
    • and Soumyaroop Bhattacharya
    Genome Res. March 1, 2003 13: 503-512; doi:10.1101/gr.104003
    ...sets of genes), and even oral replacement therapy, as in the case of the effects of oral replacement of guanylin on colon cancer rates in mice ( Shailubhai et al. 2000 ). The route to discovery includes gene expression profiling of known types → identification of biomarkers (dysregulated genes...
  5. Methods: Classification of a large microarray data set: Algorithm comparison and analysis of drug signatures
    • Georges Natsoulis,
    • Laurent El Ghaoui,
    • Gert R.G. Lanckriet,
    • Alexander M. Tolley,
    • Fabrice Leroy,
    • Shane Dunlea,
    • Barrett P. Eynon,
    • Cecelia I. Pearson,
    • Stuart Tugendreich,
    • and Kurt Jarnagin
    Genome Res. May 2005 15: 724-736; doi:10.1101/gr.2807605
    ...are combined with feature selection techniques that further reduce the length of the drug signatures, an important step towards the development of useful diagnostic biomarkers and low-cost assays. Multiple signatures with no genes in common can be generated for the same classification end-point. Comparison...
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