{"title":"通过整合基因组学和时间注释追踪人类特征进化。","authors":"Jian Zeng","doi":"10.1016/j.xgen.2025.100767","DOIUrl":null,"url":null,"abstract":"<p><p>Understanding the evolution of human traits is a fundamental yet challenging question. In a recent Cell Genomics article, Kun et al.<sup>1</sup> integrate large-scale genomic and phenotypic data, including deep-learning-derived imaging phenotypes, with temporal annotations to estimate the timing of evolutionary changes that led to differences in traits between modern humans and primates or hominin ancestors.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100767"},"PeriodicalIF":11.1000,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11872422/pdf/","citationCount":"0","resultStr":"{\"title\":\"Tracing human trait evolution through integrative genomics and temporal annotations.\",\"authors\":\"Jian Zeng\",\"doi\":\"10.1016/j.xgen.2025.100767\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Understanding the evolution of human traits is a fundamental yet challenging question. In a recent Cell Genomics article, Kun et al.<sup>1</sup> integrate large-scale genomic and phenotypic data, including deep-learning-derived imaging phenotypes, with temporal annotations to estimate the timing of evolutionary changes that led to differences in traits between modern humans and primates or hominin ancestors.</p>\",\"PeriodicalId\":72539,\"journal\":{\"name\":\"Cell genomics\",\"volume\":\" \",\"pages\":\"100767\"},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2025-02-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11872422/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell genomics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.xgen.2025.100767\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/24 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell genomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.xgen.2025.100767","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/24 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
Tracing human trait evolution through integrative genomics and temporal annotations.
Understanding the evolution of human traits is a fundamental yet challenging question. In a recent Cell Genomics article, Kun et al.1 integrate large-scale genomic and phenotypic data, including deep-learning-derived imaging phenotypes, with temporal annotations to estimate the timing of evolutionary changes that led to differences in traits between modern humans and primates or hominin ancestors.
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