Author

Jongkwon Jo

Gyeongsang National University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Mingon KangiD· 2 shared Beomsu BaekiD· 1 shared Joong-Yang ParkiD· 1 shared Seungha Jung· 1 shared Young Soon KimiD· 1 shared Youngsoon Kim· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 9 mutual co-author links

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2 shared papersBioinformatics

Mingon KangORCID

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2 papers

Recent·Most cited

Stochastic LASSO for extremely high-dimensional genomic data

Beomsu Baek, Jongkwon Jo, Mingon Kang, Youngsoon Kim

The paper introduces Stochastic LASSO, a bootstrap-based method for feature selection in high-dimensional genomic data, showing improved performance over existing models in simulation and real cancer data.

Scientific Reports · Jan 14, 2026Peer-reviewedBioinformatics

Hi-LASSO: High-performance Python and Apache spark packages for feature selection with high-dimensional data

Jongkwon Jo, Seungha Jung, Joong-Yang Park, Young Soon Kim, Mingon Kang

Hi-LASSO provides Python and Apache Spark packages for efficient feature selection in high-dimensional data, with improved performance and scalability through parallel implementation and parametric statistical tests.

PLoS ONE · Dec 1, 2022Peer-reviewedBioinformatics