Light microscopy applications in systems biology: opportunities and challenges

被引：28

作者：

Antony, Paul Michel Aloyse ^{[1
]}

Trefois, Christophe ^{[1
]}

Stojanovic, Aleksandar ^{[2
]}

Baumuratov, Aidos Sagatovich ^{[1
]}

Kozak, Karol ^{[3
,4
]}

机构：

[1] Univ Luxembourg, LCSB, Esch Sur Alzette, Luxembourg

[2] Univ Luxembourg, Interdisciplinary Ctr Secur Reliabil & Trust SnT, Luxembourg, Luxembourg

[3] ETH, Inst Biochem, Light Microscopy Ctr LMSC, Zurich, Switzerland

[4] Tech Univ Dresden, Fac Med, D-01062 Dresden, Germany

来源：

CELL COMMUNICATION AND SIGNALING | 2013年 / 11卷

关键词：

Microscopy; Systems biology; Image analysis; Segmentation; Features; Machine learning; GENOME-WIDE RNAI; HIGH-THROUGHPUT; FLUORESCENCE MICROSCOPY; CAENORHABDITIS-ELEGANS; BIOIMAGE INFORMATICS; IMAGE-ANALYSIS; C; ELEGANS; QUANTITATIVE-ANALYSIS; AUTOMATIC IDENTIFICATION; COMPUTATIONAL TOOL;

D O I：

10.1186/1478-811X-11-24

中图分类号：

Q2 [细胞生物学];

学科分类号：

071009 ; 090102 ;

摘要：

Biological systems present multiple scales of complexity, ranging from molecules to entire populations. Light microscopy is one of the least invasive techniques used to access information from various biological scales in living cells. The combination of molecular biology and imaging provides a bottom-up tool for direct insight into how molecular processes work on a cellular scale. However, imaging can also be used as a top-down approach to study the behavior of a system without detailed prior knowledge about its underlying molecular mechanisms. In this review, we highlight the recent developments on microscopy-based systems analyses and discuss the complementary opportunities and different challenges with high-content screening and high-throughput imaging. Furthermore, we provide a comprehensive overview of the available platforms that can be used for image analysis, which enable community-driven efforts in the development of image-based systems biology.

引用

页数：19

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