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Author Correction: Benchmarking machine learning methods for synthetic lethality prediction in cancer.

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Title: Author Correction: Benchmarking machine learning methods for synthetic lethality prediction in cancer.
Authors: Feng Y; School of Information Science and Technology, ShanghaiTech University, Shanghai, China.; Lingang Laboratory, Shanghai, China., Long Y; Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore., Wang H; School of Information Science and Technology, ShanghaiTech University, Shanghai, China., Ouyang Y; School of Information Science and Technology, ShanghaiTech University, Shanghai, China., Li Q; School of Information Science and Technology, ShanghaiTech University, Shanghai, China., Wu M; Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore. wumin@i2r.a-star.edu.sg., Zheng J; School of Information Science and Technology, ShanghaiTech University, Shanghai, China. zhengjie@shanghaitech.edu.cn.; Shanghai Engineering Research Center of Intelligent Vision and Imaging, Shanghai, China. zhengjie@shanghaitech.edu.cn.
Source: Nature communications [Nat Commun] 2025 Feb 13; Vol. 16 (1), pp. 1619. Date of Electronic Publication: 2025 Feb 13.
Publication Type: Published Erratum
Journal Info: Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE; PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: Author Correction: Benchmarking machine learning methods for synthetic lethality prediction in cancer.
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  Data: <searchLink fieldCode="AU" term="%22Feng+Y%22">Feng Y</searchLink>; School of Information Science and Technology, ShanghaiTech University, Shanghai, China.; Lingang Laboratory, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Long+Y%22">Long Y</searchLink>; Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.<br /><searchLink fieldCode="AU" term="%22Wang+H%22">Wang H</searchLink>; School of Information Science and Technology, ShanghaiTech University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Ouyang+Y%22">Ouyang Y</searchLink>; School of Information Science and Technology, ShanghaiTech University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Li+Q%22">Li Q</searchLink>; School of Information Science and Technology, ShanghaiTech University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Wu+M%22">Wu M</searchLink>; Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore. wumin@i2r.a-star.edu.sg.<br /><searchLink fieldCode="AU" term="%22Zheng+J%22">Zheng J</searchLink>; School of Information Science and Technology, ShanghaiTech University, Shanghai, China. zhengjie@shanghaitech.edu.cn.; Shanghai Engineering Research Center of Intelligent Vision and Imaging, Shanghai, China. zhengjie@shanghaitech.edu.cn.
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  Data: <searchLink fieldCode="JN" term="%22101528555%22">Nature communications</searchLink> [Nat Commun] 2025 Feb 13; Vol. 16 (1), pp. 1619. <i>Date of Electronic Publication: </i>2025 Feb 13.
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