Optimal alpha reduces error rates in gene expression studies - NCBI
www.ncbi.nlm.nih.gov › PMC5480162
Jun 21, 2017 · Optimal alpha reduces error rates in gene expression ... False discovery rate paradigms for statistical analyses of microarray gene expression ...
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Sep 20, 2005 · This method is applied to data sets involving diabetes, inflammatory myopathies, and Alzheimer's disease, using gene sets we compiled from ...
Jul 6, 2023 · The basic framework is demonstrated by curated analyses of microarray datasets from human studies available in the Gene Expression Omnibus (GEO) ...
In this study, an improved ensemble learning-based method, MSPJ (the Joint method of Meta-analysis, SVM-RFE, and Permutation test) was proposed to discover DEGs ...
Nov 18, 2022 · Oncology Bioinformatics project tutorial-Differential gene expression and Biomarker discovery analysis using Colorectal Cancer dataset.
Abstract. A basic task in the analysis of count data from RNA-seq is the detection of differentially expressed genes. The count data are ...
Dec 26, 2019 · First, we use domain knowledge in quantitative trading to design the sampling rules and object function. Second, pre-training and model pruning ...
May 2, 2023 · Many statistical methods have been developed to explore correlation/association between transcripts in RNA-seq data, including the 'weighted ...
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Aug 11, 2020 · Gene ontology (GO) and KEGG pathway enrichment analysis of the genes containing breed-specific SNPs was performed using EnrichR to explore the ...
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