Bioimage informatics: a new area of engineering biology.

Bioimage informatics: a new area of engineering biology.
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生物图像信息学:工程生物学的新领域。

DOI:
10.1093/bioinformatics/btn346
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发表时间:
2008-09-01
期刊:
影响因子:
5.8
通讯作者:
Peng, Hanchuan
Peng, Hanchuan
中科院分区:
生物学3区
文献类型:
--
作者:
Peng, Hanchuan

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近年来,大量复杂的分子和细胞显微图像给图像计算界带来了巨大的挑战。在这些数据密集型问题中,人们越来越关注开发新的图像处理、数据挖掘、数据库和可视化技术来提取、比较、搜索和管理生物知识。这一新兴的生物信息学领域可以被称为“生物图像信息学”。本文从应用领域、关键技术、可用工具和资源等几个方面综述了该领域的研究进展。应用实例,如高通量/高内容的表型和模式生物图谱的建立证明了生物图像信息学的重要性。这些应用程序的成功,如生物图像特征识别,分割和跟踪,注册,注释,挖掘,图像数据管理和可视化的基本技术,进一步总结,沿着与可用的生物图像数据库,分析工具和其他资源的简要概述。联系方式:www.example.com补充信息:补充数据可从生物信息学在线网站获得。
In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called ‘bioimage informatics’. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources. Contact: pengh@janelia.hhmi.org Supplementary information: Supplementary data are available at Bioinformatics online.
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