Open source bioimage informatics for cell biology

被引:34
|
作者
Swedlow, Jason R. [1 ]
Eliceiri, Kevin W. [2 ,3 ]
机构
[1] Univ Dundee, Coll Life Sci, Wellcome Trust Ctr Gene Regulat & Express, Dundee DD1 5EH, Scotland
[2] Univ Wisconsin, Lab Opt & Computat Instrumentat, Dept Mol Biol, Grad Sch, Madison, WI 53706 USA
[3] Univ Wisconsin, Grad Sch, Dept Biomed Engn, Madison, WI 53706 USA
基金
英国生物技术与生命科学研究理事会; 英国工程与自然科学研究理事会; 英国惠康基金;
关键词
OPEN MICROSCOPY ENVIRONMENT; GREEN FLUORESCENT PROTEIN; IMAGE DATA; QUANTITATIVE-ANALYSIS; OPEN TOOLS; SEGMENTATION; DATABASE; QUANTIFICATION; VISUALIZATION; MEMBRANE;
D O I
10.1016/j.tcb.2009.08.007
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Significant technical advances in imaging, molecular biology and genomics have fueled a revolution in cell biology, in that the molecular and structural processes of the cell are now visualized and measured routinely. Driving much of this recent development has been the advent of computational tools for the acquisition, visualization, analysis and dissemination of these datasets. These tools collectively make up a new subfield of computational biology called bioimage informatics, which is facilitated by open source approaches. We discuss why open source tools for image informatics in cell biology are needed, some of the key general attributes of what make an open source imaging application successful, and point to opportunities for further operability that should greatly accelerate future cell biology discovery.
引用
收藏
页码:656 / 660
页数:5
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