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  1. 1
    Phylogenetic and population structure analysis.

    Phylogenetic and population structure analysis. by Ka Wo Wong (18625847)

    Published 2024
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  2. 2
    EAT-Rice: A predictive model for flanking gene expression of T-DNA insertion activation-tagged rice mutants by machine learning approaches

    EAT-Rice: A predictive model for flanking gene expression of T-DNA insertion activation-tagged rice mutants by machine learning approaches by Chi-Chou Liao (6680852)

    Published 2019
    “…<div><p>T-DNA activation-tagging technology is widely used to study rice gene functions. When T-DNA inserts into genome, the flanking gene expression may be altered using CaMV 35S enhancer, but the affected genes still need to be validated by biological experiment. …”
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  3. 3
    DataSheet_1_A Five-MicroRNA Signature Predicts the Prognosis in Nasopharyngeal Carcinoma.docx

    DataSheet_1_A Five-MicroRNA Signature Predicts the Prognosis in Nasopharyngeal Carcinoma.docx by Shixiong Wu (11413208)

    Published 2021
    “…Background<p>There is no effective prognostic signature that could predict the prognosis of nasopharyngeal carcinoma (NPC).</p>Methods<p>We constructed a prognostic signature based on five microRNAs using random forest and Least Absolute Shrinkage And Selection Operator (LASSO) algorithm on the GSE32960 cohort (N = 213). …”
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  4. 4
    DataSheet_2_A Five-MicroRNA Signature Predicts the Prognosis in Nasopharyngeal Carcinoma.xlsx

    DataSheet_2_A Five-MicroRNA Signature Predicts the Prognosis in Nasopharyngeal Carcinoma.xlsx by Shixiong Wu (11413208)

    Published 2021
    “…Background<p>There is no effective prognostic signature that could predict the prognosis of nasopharyngeal carcinoma (NPC).</p>Methods<p>We constructed a prognostic signature based on five microRNAs using random forest and Least Absolute Shrinkage And Selection Operator (LASSO) algorithm on the GSE32960 cohort (N = 213). …”
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