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Sungroh Yoon on Muck Rack

Sungroh Yoon

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Articles

Author Correction: AIVariant: a deep learning-based somatic variant detector for highly contaminated tumor samples - Experimental & Molecular Medicine

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By Sun Il Kim, Sungroh Yoon
| Nature Verified
Correction to: Experimental & Molecular Medicine (2023) 55: 1734–1742 https://doi.org/10.1038/s12276-023-01049-2; Article published online 01 August 2023 In this Article, the funding from ‘the Technology development Program, funded by the Ministry of SMEs and Startups, Republic of Korea (RS-2023-00258711)’ was omitted. The correct statement of this Article should have read as below. “We express our gratitude to Sangho Park from Genome4me Inc.
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Author Correction: Predicting the efficiency of prime editing guide RNAs in human cells - Nature Biotechnology

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By Hui Kwon Kim, Goosang Yu, Sungroh Yoon
| Nature Verified
Correction to: Nature Biotechnology https://doi.org/10.1038/s41587-020-0677-y, published online 21 September 2020. In the version of the article initially published, there was an error in Fig. 4: panel d was a duplicate of panel c. This has now been corrected in the HTML and PDF versions of the article. About this article Kim, H.K., Yu, G., Park, J. et al. Author Correction: Predicting the efficiency of prime editing guide RNAs in human cells. Nat Biotechnol (2024).
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AIVariant: a deep learning-based somatic variant detector for highly contaminated tumor samples - Experimental & Molecular Medicine

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By Sun Il Kim, Sungroh Yoon
| Nature Verified
Abstract The detection of somatic DNA variants in tumor samples with low tumor purity or sequencing depth remains a daunting challenge despite numerous attempts to address this problem. In this study, we constructed a substantially extended set of actual positive variants originating from a wide range of tumor purities and sequencing depths, as well as actual negative variants derived from sequencer-specific sequencing errors.
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