Author

Somang Kim

University of Illinois Urbana-Champaign

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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Genomics· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Assay:CRISPR screen· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Assay:proteomics· 1

Frequent Co-Authors

Jun S. SongiD· 3 shared Pablo Pérez‐PiñeraiD· 2 shared Wendy S. WoodsiD· 2 shared Alan LuuiD· 1 shared Alex Finnegan· 1 shared Destry A. Newton· 1 shared Hu JiniD· 1 shared Jacob R. Leistico· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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3 shared papersGenomics

Jun S. SongORCID

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Author profile →

3 papers

Recent·Most cited

Chromatin structure and context-dependent sequence features control prime editing efficiency

Somang Kim, Jimmy B. Yuan, Wendy S. Woods, Destry A. Newton, Pablo Pérez‐Piñera, Jun S. Song

This study identifies epigenomic and sequence features that influence prime editing efficiency and provides guidelines for optimizing prime editor designs.

Frontiers in Genetics · Jun 29, 2023Peer-reviewedGenomics

Predicting TCR-epitope Binding Specificity Using Deep Metric Learning and Multimodal Learning

Alan Luu, Jacob R. Leistico, Timothy J. Miller, Somang Kim, Jun S. Song

This paper predicts TCR-epitope binding specificity using deep metric learning and multimodal learning, revealing key amino acid patterns and challenging assumptions about physical proximity.

Genes · Apr 15, 2021Peer-reviewedBioinformatics

Epigenetic engineering of yeast reveals dynamic molecular adaptation to methylation stress and genetic modulators of specific DNMT3 family members

Alex Finnegan, Somang Kim, Hu Jin, Michael Gapinske, Wendy S. Woods, Pablo Pérez‐Piñera, Jun S. Song

This study uses yeast to investigate how DNA methylation is regulated by DNMT3 family members and identifies sequence preferences and spatial patterns of methylation.

Nucleic Acids Research · Mar 13, 2020Peer-reviewedGenomics