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中文摘要
翻译
为了从基因组学的大数据中获得最大利益,生物学家需要软件工具来增强我们的信息, 天生的认知和视觉能力。我们的视觉和认知系统拥有非凡的能力, 识别模式,可视化分析软件应用程序旨在通过提供 可视化的、交互式的数据接口。我的研究重点是开发可视化分析工具, 为生命科学家提供相关资源,使用集成基因组浏览器作为交付平台, 实验集成基因组浏览器是一个快速,高度可定制,免费提供的开源 桌面基因组浏览器应用程序开发自2000年代初,现在为成千上万的 全球用户。通过为成千上万的用户开发和支持IGB,我的研究有助于 其他可视化研究程序可以并且可以做到的基因组浏览的创新新方法 建立在。在接下来的五年里,我将继续使用最先进的开源软件 开发方法适合于学术环境,以低成本构建和发布高级工具, 同时培训计算机科学和生物信息学方面的学生。第一,我会不断开拓新的途径 利用新兴的公共和私有云基础设施来满足生物学家日益复杂的需求 高级可视化分析。使用商业和免费的公共部门云平台, 我和我的学生将尝试将集成基因组浏览器连接到存储和可视化 分析计算能力超过了在单个台式计算机上可能实现的能力。 IGB中的这些高级功能将通过演示如何 应用程序开发人员可以利用云的力量来可视化数据。第二,我将继续 将IGB和相关工具构建成一个平台,其他开发人员可以利用和学习。领域 基因组学变化很快。随着新的方法和工具上线,开发人员需要一些方法来创建 新的可视化工具适合这些新方法。我的研究旨在提供一个平台, 这将使生物信息学的开发人员能够构建和发布新的可视化分析 算法更快地向更多的潜在用户。我的团队将继续发展, 支持IGB的应用程序商店,这是一个在线交换中心,供开发人员分发应用程序,供用户 查找并安装与他们的研究相关的应用程序。为了支持开发人员,我们将继续改进IGB的 内部应用程序编程接口(API),一组精心设计的方法和类, 具有不同技能和知识的开发人员向IGB接口添加新功能和特性。第三、 我和我的学生将继续探索社区、开源软件等更大的概念, 开发和人性化的软件设计,将工具构建者与工具用户联系起来, 合作和创新,造福所有人。
英文摘要
To gain maximum benefit from big data in genomics, biologists need software tools that enhance our in- born cognitive and visual faculties. Our visual and cognitive systems possess extraordinary power to recognize patterns, and visual analytics software applications aim to enhance this ability by providing visual, interactive interfaces to data. My research focuses on developing visual analytics tools and associated resources for life scientists, using Integrated Genome Browser as a platform for delivery and experimentation. Integrated Genome Browser is a fast, highly customizable, freely available open source desktop genome browser application developed since the early 2000s that now serves thousands of users worldwide. By developing and supporting IGB for its thousands of users, my research contributes innovative new approaches for genome browsing that other visualization research programs can and do build upon. During the next five years, I will continue using state-of-the-art open source software development methods adapted to an academic setting to build and release advanced tools at low cost, while training students in computer science and bioinformatics. First, I will continue to develop new ways to exploit emerging public and private cloud infrastructure to meet biologists’ increasingly complex needs for advanced visual analytics. Using commercial and free-of-charge, public sector cloud platforms, my students and I will experiment with connecting Integrated Genome Browser to storage and visual analytics computing capability exceeding what is possible to achieve on a single, desktop computer. These advanced features within IGB will help move the entire field forward by demonstrating how application developers can harness the power of the cloud for visualizing data. Second, I will continue to build IGB and related tools into a platform that other developers can exploit and learn from. The field of genomics changes rapidly. As new methods and tools come on-line, developers need ways to create new visualization tools suited to these new methods. My research aims to provide a platform for experimentation that will enable developers in bioinformatics to build and release new visual analytics algorithms more rapidly to larger numbers of potential users. My group will continue to develop and support an App Store for IGB, an on-line clearinghouse for developers to distribute Apps and for users to find and install Apps relevant to their research. To support developers, we will continue to improve IGB’s internal application programmer’s interface (API), a collection of methods and classes crafted to enable developers of varying skill and knowledge to add new functions and features to the IGB interface. Third, my students and I will continue to explore larger concepts of community, open source software development, and humane software design by connecting tool builders with tool users to promote collaboration and innovation for the benefit of all.
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会议论文
Visualization software for genomics
Linking Integrated Genome Browser and CyVerse
Linking Integrated Genome Browser and CyVerse
Continued Maintenance and Development of Software: Integrated Genome Browser and
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis