基于图像的扰动分析中的应用。

Applications in image-based profiling of perturbations.

作者信息

Caicedo Juan C, Singh Shantanu, Carpenter Anne E

机构信息

Imaging Platform of the Broad Institute of Harvard and Massachusetts Institute of Technology, 415 Main Street, Cambridge, MA, USA; Fundación Universitaria Konrad Lorenz, Bogotá, Colombia.

Imaging Platform of the Broad Institute of Harvard and Massachusetts Institute of Technology, 415 Main Street, Cambridge, MA, USA.

出版信息

Curr Opin Biotechnol. 2016 Jun;39:134-142. doi: 10.1016/j.copbio.2016.04.003. Epub 2016 Apr 17.

DOI:10.1016/j.copbio.2016.04.003

PMID:27089218

Abstract

A dramatic shift has occurred in how biologists use microscopy images. Whether experiments are small-scale or high-throughput, automatically quantifying biological properties in images is now widespread. We see yet another revolution under way: a transition towards using automated image analysis to not only identify phenotypes a biologist specifically seeks to measure ('screening') but also as an unbiased and sensitive tool to capture a wide variety of subtle features of cell (or organism) state ('profiling'). Mapping similarities among samples using image-based (morphological) profiling has tremendous potential to transform drug discovery, functional genomics, and basic biological research. Applications include target identification, lead hopping, library enrichment, functionally annotating genes/alleles, and identifying small molecule modulators of gene activity and disease-specific phenotypes.

摘要

生物学家使用显微镜图像的方式发生了巨大转变。无论实验是小规模的还是高通量的，现在自动量化图像中的生物学特性都很普遍。我们正在目睹另一场革命：向使用自动图像分析的转变，不仅用于识别生物学家专门想要测量的表型（“筛选”），还作为一种无偏见且灵敏的工具来捕捉细胞（或生物体）状态的各种细微特征（“剖析”）。使用基于图像的（形态学）剖析来绘制样本之间的相似性，在变革药物发现、功能基因组学和基础生物学研究方面具有巨大潜力。其应用包括靶点识别、先导化合物跳跃、文库富集、对基因/等位基因进行功能注释，以及识别基因活性和疾病特异性表型的小分子调节剂。