Hasil Pencarian - Jingyi Jessica Li

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  1. 1
    PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data

    PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data oleh Dongyuan Song, Jingyi Jessica Li

    Diterbitkan 2021-04-01
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  2. 2
    Statistical Hypothesis Testing versus Machine Learning Binary Classification: Distinctions and Guidelines

    Statistical Hypothesis Testing versus Machine Learning Binary Classification: Distinctions and Guidelines oleh Jingyi Jessica Li, Xin Tong

    Diterbitkan 2020-10-01
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  3. 3
    Exploring the optimization of autoencoder design for imputing single-cell RNA sequencing data

    Exploring the optimization of autoencoder design for imputing single-cell RNA sequencing data oleh Nan Miles Xi, Jingyi Jessica Li

    Diterbitkan 2023-01-01
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  4. 4
    Protocol for executing and benchmarking eight computational doublet-detection methods in single-cell RNA sequencing data analysis

    Protocol for executing and benchmarking eight computational doublet-detection methods in single-cell RNA sequencing data analysis oleh Nan Miles Xi, Jingyi Jessica Li

    Diterbitkan 2021-09-01
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  5. 5
    An accurate and robust imputation method scImpute for single-cell RNA-seq data

    An accurate and robust imputation method scImpute for single-cell RNA-seq data oleh Wei Vivian Li, Jingyi Jessica Li

    Diterbitkan 2018-03-01
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  6. 6
    Statistical method scDEED for detecting dubious 2D single-cell embeddings and optimizing t-SNE and UMAP hyperparameters

    Statistical method scDEED for detecting dubious 2D single-cell embeddings and optimizing t-SNE and UMAP hyperparameters oleh Lucy Xia, Christy Lee, Jingyi Jessica Li

    Diterbitkan 2024-02-01
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  7. 7
    scReadSim: a single-cell RNA-seq and ATAC-seq read simulator

    scReadSim: a single-cell RNA-seq and ATAC-seq read simulator oleh Guanao Yan, Dongyuan Song, Jingyi Jessica Li

    Diterbitkan 2023-11-01
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  8. 8
    mbImpute: an accurate and robust imputation method for microbiome data

    mbImpute: an accurate and robust imputation method for microbiome data oleh Ruochen Jiang, Wei Vivian Li, Jingyi Jessica Li

    Diterbitkan 2021-06-01
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  9. 9
    System wide analyses have underestimated protein abundances and the importance of transcription in mammals

    System wide analyses have underestimated protein abundances and the importance of transcription in mammals oleh Jingyi Jessica Li, Peter J. Bickel, Mark D. Biggin

    Diterbitkan 2014-02-01
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  10. 10
    Statistics or biology: the zero-inflation controversy about scRNA-seq data

    Statistics or biology: the zero-inflation controversy about scRNA-seq data oleh Ruochen Jiang, Tianyi Sun, Dongyuan Song, Jingyi Jessica Li

    Diterbitkan 2022-01-01
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  11. 11
    Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes

    Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes oleh Jingyi Jessica Li, Guo-Liang Chew, Mark Douglas Biggin

    Diterbitkan 2019-08-01
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  12. 12
    Publisher Correction: scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured

    Publisher Correction: scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured oleh Tianyi Sun, Dongyuan Song, Wei Vivian Li, Jingyi Jessica Li

    Diterbitkan 2021-06-01
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  13. 13
    scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured

    scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured oleh Tianyi Sun, Dongyuan Song, Wei Vivian Li, Jingyi Jessica Li

    Diterbitkan 2021-05-01
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  14. 14
    Author Correction: scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured

    Author Correction: scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured oleh Tianyi Sun, Dongyuan Song, Wei Vivian Li, Jingyi Jessica Li

    Diterbitkan 2023-02-01
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  15. 15
    Exaggerated false positives by popular differential expression methods when analyzing human population samples

    Exaggerated false positives by popular differential expression methods when analyzing human population samples oleh Yumei Li, Xinzhou Ge, Fanglue Peng, Wei Li, Jingyi Jessica Li

    Diterbitkan 2022-03-01
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  16. 16
    Identifying the combinatorial control of signal-dependent transcription factors.

    Identifying the combinatorial control of signal-dependent transcription factors. oleh Ning Wang, Diane Lefaudeux, Anup Mazumder, Jingyi Jessica Li, Alexander Hoffmann

    Diterbitkan 2021-06-01
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  17. 17
    PCA outperforms popular hidden variable inference methods for molecular QTL mapping

    PCA outperforms popular hidden variable inference methods for molecular QTL mapping oleh Heather J. Zhou, Lei Li, Yumei Li, Wei Li, Jingyi Jessica Li

    Diterbitkan 2022-10-01
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  18. 18
    scCDC: a computational method for gene-specific contamination detection and correction in single-cell and single-nucleus RNA-seq data

    scCDC: a computational method for gene-specific contamination detection and correction in single-cell and single-nucleus RNA-seq data oleh Weijian Wang, Yihui Cen, Zezhen Lu, Yueqing Xu, Tianyi Sun, Ying Xiao, Wanlu Liu, Jingyi Jessica Li, Chaochen Wang

    Diterbitkan 2024-05-01
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  19. 19
    The concurrence of DNA methylation and demethylation is associated with transcription regulation

    The concurrence of DNA methylation and demethylation is associated with transcription regulation oleh Jiejun Shi, Jianfeng Xu, Yiling Elaine Chen, Jason Sheng Li, Ya Cui, Lanlan Shen, Jingyi Jessica Li, Wei Li

    Diterbitkan 2021-09-01
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  20. 20
    Machine learning predicts improvement of functional outcomes in traumatic brain injury patients after inpatient rehabilitation

    Machine learning predicts improvement of functional outcomes in traumatic brain injury patients after inpatient rehabilitation oleh Irene Say, Yiling Elaine Chen, Matthew Z. Sun, Jingyi Jessica Li, Daniel C. Lu, Daniel C. Lu, Daniel C. Lu

    Diterbitkan 2022-09-01
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