{"title":"MitoNet:一个在电子显微镜数据集中分割单个线粒体的通用模型。","authors":"Brian Glancy","doi":"10.1016/j.cels.2022.12.004","DOIUrl":null,"url":null,"abstract":"<p><p>Volume electron microscopy provides a powerful approach to investigating physical connectivity within biological systems. In an article in this issue of Cell Systems, Conrad and Narayan overcome a major hurdle in volume electron microscopy by developing \"MitoNet,\" a broadly applicable model for labeling individual mitochondria across volume electron microscopy datasets.</p>","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":"14 1","pages":"7-8"},"PeriodicalIF":9.0000,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MitoNet: A generalizable model for segmentation of individual mitochondria within electron microscopy datasets.\",\"authors\":\"Brian Glancy\",\"doi\":\"10.1016/j.cels.2022.12.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Volume electron microscopy provides a powerful approach to investigating physical connectivity within biological systems. In an article in this issue of Cell Systems, Conrad and Narayan overcome a major hurdle in volume electron microscopy by developing \\\"MitoNet,\\\" a broadly applicable model for labeling individual mitochondria across volume electron microscopy datasets.</p>\",\"PeriodicalId\":54348,\"journal\":{\"name\":\"Cell Systems\",\"volume\":\"14 1\",\"pages\":\"7-8\"},\"PeriodicalIF\":9.0000,\"publicationDate\":\"2023-01-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell Systems\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1016/j.cels.2022.12.004\",\"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":"Cell Systems","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.cels.2022.12.004","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}
MitoNet: A generalizable model for segmentation of individual mitochondria within electron microscopy datasets.
Volume electron microscopy provides a powerful approach to investigating physical connectivity within biological systems. In an article in this issue of Cell Systems, Conrad and Narayan overcome a major hurdle in volume electron microscopy by developing "MitoNet," a broadly applicable model for labeling individual mitochondria across volume electron microscopy datasets.
Cell SystemsMedicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍：
In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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