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Bioinformatics (Oxford, England)|February 22, 2020
netGO: R-Shiny package for network-integrated pathway enrichment analysisJinhwan Kim, Sora Yoon, Dougu NamBMC Genomics|May 27, 2017
Gene dispersion is the key determinant of the read count bias in differential expression analysis of RNA-seq dataSora Yoon, Dougu NamPlos One|May 1, 2020
Benchmarking RNA-seq differential expression analysis methods using spike-in and simulation dataBukyung Baik, Sora Yoon, Dougu NamPlos One|November 10, 2016
Improving Gene-Set Enrichment Analysis of RNA-Seq Data with Small ReplicatesSora Yoon, Seon-Young Kim, Dougu NamBMC Genomics|May 11, 2019
GScluster: network-weighted gene-set clustering analysisSora Yoon, Jinhwan Kim, Seon-Kyu Kim, et al.Scientific Reports|March 27, 2021
Powerful p-value combination methods to detect incomplete associationSora Yoon, Bukyung Baik, Taesung Park, et al.Nucleic Acids Research|March 2, 2019
Biclustering analysis of transcriptome big data identifies condition-specific microRNA targetsSora Yoon, Hai C T Nguyen, Woobeen Jo, et al.Nucleic Acids Research|March 22, 2018
Efficient pathway enrichment and network analysis of GWAS summary data using GSA-SNP2Sora Yoon, Hai C T Nguyen, Yun J Yoo, et al.Nature Communications|March 22, 2023
Benchmarking integration of single-cell differential expressionHai C T Nguyen, Bukyung Baik, Sora Yoon, et al.Bioinformatics (Oxford, England)|September 9, 2010
De-correlating expression in gene-set analysisDougu NamPageof 15