{"title":"用预测因子解锁蛋白质网络：SPOC优势","authors":"Arne Elofsson","doi":"10.1016/j.molcel.2025.02.010","DOIUrl":null,"url":null,"abstract":"In this issue of <em>Molecular Cell</em>, Schmid and Walter present “Predictomes,”<span><span><sup>1</sup></span></span> a machine-learning-based platform that utilizes AlphaFold-Multimer (AF-M) to identify high-confidence protein-protein interactions (PPIs). Their SPOC classifier is better than existing methods at separating true and false interactions.","PeriodicalId":18950,"journal":{"name":"Molecular Cell","volume":"14 1","pages":""},"PeriodicalIF":16.6000,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unlocking protein networks with Predictomes: The SPOC advantage\",\"authors\":\"Arne Elofsson\",\"doi\":\"10.1016/j.molcel.2025.02.010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this issue of <em>Molecular Cell</em>, Schmid and Walter present “Predictomes,”<span><span><sup>1</sup></span></span> a machine-learning-based platform that utilizes AlphaFold-Multimer (AF-M) to identify high-confidence protein-protein interactions (PPIs). Their SPOC classifier is better than existing methods at separating true and false interactions.\",\"PeriodicalId\":18950,\"journal\":{\"name\":\"Molecular Cell\",\"volume\":\"14 1\",\"pages\":\"\"},\"PeriodicalIF\":16.6000,\"publicationDate\":\"2025-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular Cell\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1016/j.molcel.2025.02.010\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Cell","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.molcel.2025.02.010","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Unlocking protein networks with Predictomes: The SPOC advantage
In this issue of Molecular Cell, Schmid and Walter present “Predictomes,”1 a machine-learning-based platform that utilizes AlphaFold-Multimer (AF-M) to identify high-confidence protein-protein interactions (PPIs). Their SPOC classifier is better than existing methods at separating true and false interactions.
期刊介绍：
Molecular Cell is a companion to Cell, the leading journal of biology and the highest-impact journal in the world. Launched in December 1997 and published monthly. Molecular Cell is dedicated to publishing cutting-edge research in molecular biology, focusing on fundamental cellular processes. The journal encompasses a wide range of topics, including DNA replication, recombination, and repair; Chromatin biology and genome organization; Transcription; RNA processing and decay; Non-coding RNA function; Translation; Protein folding, modification, and quality control; Signal transduction pathways; Cell cycle and checkpoints; Cell death; Autophagy; Metabolism.
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