Author

Hwa-Jin Lee

Seoul National UniversityORCID 0000-0001-6322-3808Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Assay:ChIP-seq· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Hong‐Gee KimiD· 2 shared Kirsten KübleriD· 2 shared Kyungsik HaiD· 2 shared Paz P PolakiD· 2 shared Aaron Lavel MoyeiD· 1 shared Alexander GuseviD· 1 shared Amnon KoreniD· 1 shared Andrew Victor BiankiniD· 1 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersBioinformatics

Hong‐Gee KimORCID

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2 papers

Recent·Most cited

BioinformaticsLifePeer-reviewedDec 27, 2022

COOBoostR: an extreme gradient boosting-based tool for robust tissue or cell-of-origin prediction of tumors

Sungmin Yang, Kyungsik Ha, Woojeung Song…·Hwa-Jin Lee

COOBoostR uses extreme gradient boosting to predict tumor tissue or cell-of-origin using chromatin marks and mutation density data, outperforming random forest methods in speed and accuracy.

9 citations

ChIP-seqbulk RNA-seq

𝕏 PostBluesky

GenomicsbioRxivPreprintJan 11, 2019

Tumor mutational landscape is a record of the pre-malignant state

Kirsten Kübler, Rosa Karlić, Nicholas J. Haradhvala…·Gad A. Getz

The paper predicts cancer cell-of-origin from DNA sequences by matching mutational landscapes to chromatin modification patterns in normal tissues.

23 citations

humanwhole-genome sequencing

𝕏 PostBluesky