{"title":"Putting proteins in context.","authors":"Mengzhou Hu, Trey Ideker","doi":"10.1016/j.cels.2024.09.009","DOIUrl":null,"url":null,"abstract":"<p><p>Proteins exhibit cell-type-specific functions and interactions, yet most ways of representing proteins lack any biological or environmental context. To address this gap, recent work by Li et al.<sup>1</sup> introduces PINNACLE, a geometric deep learning approach that generates contextualized representations of proteins by combined analysis of protein interactions and multiorgan single-cell transcriptomics.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":"15 10","pages":"891-892"},"PeriodicalIF":0.0000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.cels.2024.09.009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Proteins exhibit cell-type-specific functions and interactions, yet most ways of representing proteins lack any biological or environmental context. To address this gap, recent work by Li et al.1 introduces PINNACLE, a geometric deep learning approach that generates contextualized representations of proteins by combined analysis of protein interactions and multiorgan single-cell transcriptomics.
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