An image analysis toolbox for high-throughput C. elegans assays

被引：0

作者：

Wahlby, Carolina ^{[1
,2
]}

Kamentsky, Lee ^{[1
]}

Liu, Zihan H. ^{[1
]}

Riklin-Raviv, Tammy ^{[3
]}

Conery, Annie L. ^{[4
]}

O'Rourke, Eyleen J. ^{[4
]}

Sokolnicki, Katherine L. ^{[1
]}

Visvikis, Orane ^{[5
]}

Ljosa, Vebjorn ^{[1
]}

Irazoqui, Javier E. ^{[5
]}

Golland, Polina ^{[3
]}

Ruvkun, Gary ^{[4
]}

Ausubel, Frederick M. ^{[4
]}

Carpenter, Anne E. ^{[1
]}

机构：

[1] Broad Inst Massachusetts Inst Technol & Harvard, Cambridge, MA USA

[2] Uppsala Univ, Ctr Image Anal, Sci Life Lab, Uppsala, Sweden

[3] MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02139 USA

[4] Massachusetts Gen Hosp, Dept Mol Biol, Ctr Computat & Integrat Biol, Boston, MA 02114 USA

[5] Massachusetts Gen Hosp, Dept Pediat, Dev Immunol Program, Boston, MA 02114 USA

来源：

NATURE METHODS | 2012年 / 9卷 / 07期

基金：

美国国家卫生研究院;

关键词：

CAENORHABDITIS-ELEGANS; AUTOMATED-ANALYSIS; RESOLUTION; INSIGHTS; NEMATODE; SCREENS; MODEL;

D O I：

10.1038/NMETH.1984

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

We present a toolbox for high-throughput screening of image-based Caenorhabditis elegans phenotypes. The image analysis algorithms measure morphological phenotypes in individual worms and are effective for a variety of assays and imaging systems. This WormToolbox is available through the open-source CellProfiler project and enables objective scoring of whole-worm high-throughput image-based assays of C. elegans for the study of diverse biological pathways that are relevant to human disease.

引用

页码：714 / U273

页数：6

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