Author

Taesung Park

Seoul National UniversityORCID 0000-0002-8294-590XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Eun‐Hee KangiD· 1 shared Jaehoon AniD· 1 shared Jaeyong YeeiD· 1 shared Ji-Yeon ShiniD· 1 shared Jungsoo GimiD· 1 shared Kyungtaek ParkiD· 1 shared Minseok SeoiD· 1 shared Mira ParkiD· 1 shared

Activity by Year

2019-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

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1 shared paperBioinformatics

Eun‐Hee KangORCID

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3 papers

Recent·Most cited

BioinformaticsArchives of Microbiology & ImmunologyPeer-reviewedJan 1, 2024

Algorithm for selecting potential SARS-CoV-2 dominant variants based on POS-NT frequency

Eun‐Hee Kang, TaeJin Ahn, Taesung Park

The paper develops a DVC selection algorithm to predict SARS-CoV-2 dominant variants by analyzing POS-NT frequency trends, successfully identifying mutations for Delta and Omicron before their dominance.

DOI 10.26502/ami.936500157

viruswhole-genome sequencing

𝕏 PostBluesky

BioinformaticsPLoS ONEPeer-reviewedSep 12, 2019

Structural equation modeling for hypertension and type 2 diabetes based on multiple SNPs and multiple phenotypes

Saebom Jeon, Ji-Yeon Shin, Jaeyong Yee…·Mira Park

The paper uses structural equation modeling to analyze genetic and phenotypic relationships between SNPs, intermediate phenotypes, and diseases like hypertension and type 2 diabetes.

13 citations

humanGWAS summary statistics

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BioinformaticsBMC GenomicsPeer-reviewedJul 2, 2019

BALLI: Bartlett-Adjusted Likelihood-based LInear Model Approach for Identifying Differentially Expressed Gene with RNA-seq Data

Kyungtaek Park, Jaehoon An, Jungsoo Gim…·Sungho Won

BALLI improves differential expression analysis in RNA-seq by addressing small sample bias and providing better power and precision than existing methods.

5 citations

bulk RNA-seqstatistical model

𝕏 PostBluesky