ABI Development: BISQUE - Scalable Image Informatics for Quantitative Biology

加州大学圣巴巴拉分校获得了一项资助，用于开发基于云计算和基于网络协议的新兴范例的生物图像科学协作环境。显微成像、图像处理和计算技术的最新进展使大规模生物实验成为可能，这些实验不仅产生大量图像和视频，而且对计算和信息处理提出了新的挑战。该项目解决了关于大规模、非结构化生物图像和视频收集的核心挑战。这包括提供无处不在的图像、视频和元数据资源访问；创建易于访问的图像和视频分析，可视化和工作流程；发布数据和分析资源。利用在线虚拟环境简化团队之间的协作工作将提高科学生产力，增强对复杂现象的理解，并允许越来越多的研究人员基于迄今为止仍然是主观的图像证据来量化条件。BISQUE（生物图像语义查询和环境）开源平台正在开发中，以满足这些需求。该项目将重点关注与分析和注释相关的可扩展性问题，分布式计算和云服务的计算可扩展性，视频和3D-5D图像分析/可视化的复杂新方法，以及数据和方法的验证和管理。此外，该项目将为个别研究人员和实验室提供发布和分享数据和分析技术的手段，从而为思想的交流创造机会。该研究将为不同科学领域的图像数据管理带来新的范式。一个将立即受益的特定领域是定量生物学，其中大规模的信息定量分析将使新的科学发现和可重复的结果成为可能。Bisque平台，凭借其网络工具和对高要求计算的无缝支持，将允许不同的实验室以易于使用的形式发布科学数据集和分析。Bisque将被研究生和本科生用于教学和研究。将为本科生和高中生提供暑期研究实习机会。通过研讨会、在线教程、视频演示和iPlant发现环境，该项目将确保扩展到更广泛的研究人员。欲了解更多信息并访问Bisque平台，请访问网站http://www.bioimage.ucsb.edu/bisque。

The University of California Santa Barbara is awarded a grant to develop a collaborative environment for biological image sciences based on the emerging paradigm of cloud-computing and web-based protocols. Recent advances in microscopy imaging, image processing and computing technologies enable large-scale biological experiments that generate not only large collections of images and video, but also pose new computing and information processing challenges. This project addresses core challenges concerning large scale, unstructured biological images and video collections. These include providing ubiquitous access to images, videos and metadata resources; creating easily accessible image and video analysis, visualizations and work flows; and publishing both data and analysis resources. Streamlining collaborative efforts across teams with online virtual environments will improve scientific productivity, enhance understanding of complex phenomena and allow a growing number of researchers to quantify conditions based on image evidence that so far have remained subjective. The BISQUE (Bio-Image Semantic Query and Environment) open-source platform is being developed keeping these requirements in mind. This project will focus on scalability issues concerning analysis and annotations, computational scalability with distributed computing and cloud enabled services, sophisticated new methods for video and 3D-5D image analysis/visualization, and validation and curation of data and methods. Furthermore, the project will provide individual researchers and laboratories with the means to publish and share data and analysis techniques, thus creating opportunities for cross-fertilization of ideas.The research will lead to new paradigms for management of image data in diverse scientific fields. One specific area that will immediately benefit is quantitative biology, where large-scale quantitative analysis of information will enable new scientific discoveries and reproducible results. The Bisque platform, with its web-enabled tools and seamless support for demanding computations, will allow diverse labs to publish both scientific datasets and analysis in an easy to use form. Bisque will be used in teaching and research by graduate and undergraduate students. There will be opportunities for undergraduates and high-school students for summer research internships. Through workshops, online tutorials, video demos, and the iPlant discovery environment, this project will ensure outreach to a broader spectrum of researchers. For more information and access to the Bisque platform, visit the website at http://www.bioimage.ucsb.edu/bisque.