Modeling the vertebrate regulatory sequence landscape by UUATAC-seq and deep learningRegulatory sequence landscapes from five vertebrate species were mapped using high-resolution single-nucleus ATAC-seq. This comprehensive dataset enables a systematic interpretation of vertebrate regulatory sequence grammar through deep learning.Regulatory sequence landscapes from five vertebrate species were mapped using high-resolution single-nucleus ATAC-seq. This comprehensive dataset enables a systematic interpretation of vertebrate regulatory sequence grammar through deep learning.Xiaoping Han, Hanyu Wu, Xueyi Wang, Daiyuan Liu, Yuting Fu, Lei Yang, Renying Wang, Peijing Zhang, Jingjing Wang, Lifeng Ma, Jizhong Mao, Lina Zhou, Siqi Wang, Xinlian Zhang, Mengmeng Jiang, Xinru Wang, Guoxia Wen, Danmei Jia, Guoji Guohttps://www.cell.com/cell/fulltext/S0092-8674(25)00686-5?rss=yeshttp://www.cell.com/cell/inpress.rssCellCell RSS feed.Wireless News CampaignJuly 9, 2025

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