MitoNet: A generalizable model for segmentation of individual mitochondria within electron microscopy datasets.

IF 9 1区生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Cell Systems Pub Date : 2023-01-18 DOI:10.1016/j.cels.2022.12.004

Brian Glancy

引用次数: 0

Abstract

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.

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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。

体积电子显微镜为研究生物系统内的物理连接提供了一种强有力的方法。在本期《细胞系统》的一篇文章中，Conrad和Narayan通过开发“MitoNet”克服了体积电子显微镜的主要障碍，“MitoNet”是一种广泛适用的模型，用于在体积电子显微镜数据集上标记单个线粒体。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cell Systems Medicine-Pathology and Forensic Medicine

CiteScore

16.50

自引率

1.10%

发文量

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.