Developing tools for Bio-Molecular Image Informatics

生物分子图像信息学开发工具

• 批准号: 6944760
• 负责人: BANGALORE S MANJUNATH
• 金额: $ 14.56万
• 依托单位: MAYACHITRA, INC.
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2007-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6944760
• 关键词: bioimaging /biomedical imaging; cats; cytoskeletal proteins; data management; digital imaging; fluorescence microscopy; gene expression; genetically modified animals; green fluorescent proteins; image processing; immunofluorescence technique; information retrieval; interdisciplinary collaboration; laboratory mouse; laboratory rabbit; meta analysis; molecular /cellular imaging; molecular biology information system; retina; technology /technique development

DESCRIPTION (provided by applicant): This project brings together a strong interdisciplinary team of investigators to develop powerful image information processing and database tools for the exponentially growing bio-molecular image data, thus enabling a new generation of bio-image informatics. Contemporary microscopic techniques, including immunofluorescence microscopy, electron microscopy, GFP visualization and atomic force microscopy have ;ontributed enormously to our current understanding of molecular cell biology in its many forms. Individual research labs often generate hundreds or even thousands of images weekly. Unfortunately, most of these images are analyzed, labeled and archived manually. Further, the vast majority of these images never get published, despite the fact that many of them would be valuable for other researchers. The problems inherent in manual labeling and archiving, together with the lack of a central and searchable repository for images of all sorts (analogous to DNA sequence databases) is a major impediment to progress in essentially all fields under the general description of molecular and cellular biology. These problems also represent a major impediment to progress in the emerging area of bio-image informatics, and tools for organizing and information processing of such data are urgently needed. By coupling recent advances in image processing, pattern recognition and data mining, with the enormous amount of data that is being generated in bio-molecular imaging, significant progress can be made in our understanding of various cellular and subcelluar processes.

描述(由申请人提供)： 该项目汇集了一支强大的跨学科研究团队，为指数级增长的生物分子图像数据开发强大的图像信息处理和数据库工具，从而使新一代生物图像信息学成为可能。现代显微技术，包括免疫荧光显微镜、电子显微镜、绿色荧光蛋白可视化和原子力显微镜，极大地促进了我们目前对多种形式的分子细胞生物学的理解。个别研究实验室每周通常会产生数百甚至数千张图像。不幸的是，这些图像中的大多数都是手动分析、标记和归档的。此外，这些图像中的绝大多数从未发表过，尽管它们中的许多对其他研究人员来说是有价值的。人工标记和存档所固有的问题，再加上缺乏各种图像的中央和可搜索的储存库(类似于DNA序列数据库)，是分子和细胞生物学一般描述下的几乎所有领域取得进展的主要障碍。这些问题也是在生物图像信息学新兴领域取得进展的主要障碍，迫切需要组织和信息处理这类数据的工具。通过将图像处理、模式识别和数据挖掘方面的最新进展与生物分子成像中产生的大量数据结合起来，我们可以在理解各种细胞和亚细胞过程方面取得重大进展。