Plant Genomics Data Computational Interface

卡内基科学研究所获得了一笔赠款，用于建立一个应用程序编程接口（API），该接口将为植物基因组数据提供高性能、基于网络的计算访问。 该项目将包括一个新的、开放的技术，用于生成计算数据Web服务;一个开放的、可移植的、优化的数据仓库，支持对植物生物学数据的快速查询;以及一个植物生物学查询语言、查询构建器和查询优化器，将提供一种简单的方法，将查询结果限制在所需的数据上。该项目将提供一系列数据访问方法，以满足计算生物学家和实验室生物学家对大型和定制数据集的需求。 该软件在TAIR的实现将为TAIR数据的计算使用提供REST和SOAP Web服务，TAIR对象的RSS提要，以及TAIR新查询构建器的实现。虽然在数据生成方法（包括新基因组测序方法、高通量表型分析、蛋白质定位等）方面取得了长足的进步，但对所得数据的计算访问仍然需要大量的人力和机器资源。通过架构解决这个问题，该项目利用软件工程的进步，将它们结合并应用于植物基因组学的特定领域。特别是，开发一个最小的，但有效的植物基因组学模式，使用现代数据建模;利用模型驱动的架构，使高性能的Web服务，从平台无关的模型的生成;和开发一个基本的，格式良好的查询语言的植物基因组学领域的智力挑战性的任务，将有显着的影响所需的技术计算访问。广泛采用一套标准的网络接口来计算访问植物基因组学资源，将大大简化访问和整合植物基因组数据所需的工作，从而促进数据的计算分析。 通过提供简单、强大且一致的计算数据访问路径，标准Web界面还将促进新资源的开发，这些资源可以转换现有数据集并以新的方式呈现它们，类似于使用Google地图数据的混搭。沿着的是真实的房地产列表、天气数据、维基百科条目等。通过提供计算API和技术基础设施来将其创建为开源工具，该项目为TAIR之外的计算生物学家提供了一套关键的技术。随着这项技术证明自己，它可以超越植物生物学进入更普遍的生物学领域。关于该项目的更多信息可在TAIR网站上找到：http://arabidopsis.org。

The Carnegie Institution for Science is awarded a grant to build an application programming interface (API) that will provide high-performance, web-based computational access for plant genomics data. The project will include a new, open technology for generating computational data web services; an open, portable, optimized data warehouse that supports very fast queries of plant biology data; and a plant biology query language, query builder, and query optimizer that will provide a simple way to limit query results to only the required data. The project will provide a range of data access methods to serve the needs of computational biologists and bench biologists for large and custom datasets. Implementation of this software at TAIR will provide REST and SOAP web services for computational use of TAIR data, RSS feeds for TAIR objects, and an implementation of a new query builder for TAIR. While strong advances have been made in data generation methods including new genome sequencing methods, high throughput phenotyping, protein localization and others, computational access to the resulting data still requires large amounts of both human and machine resources. By addressing this issue through architecture, this project leverages advances in software engineering by combining and applying them to the specific domain of plant genomics. In particular, developing a minimal but effective plant genomics schema using modern data modeling; leveraging model-driven architecture to enable generation of high-performance web services from platform-independent models; and developing a basic, well-formed query language for the plant genomics domain are intellectually challenging tasks that will have a significant impact on the technology required for computational access. Wide adoption of a standard set of web interfaces for computational access to plant genomics resources will greatly simplify the effort required to access and integrate plant genomic data, thereby facilitating computational analyses of the data. By providing an easy, robust, and consistent route to computational data access, standard web interfaces will also facilitate development of new resources that could transform existing datasets and present them in new ways, analogous to mashups using Google Maps data along with real estate listings, weather data, Wikipedia entries, etc. By providing computational APIs and the technological infrastructure to create them as open source tools, this project makes available a key set of technologies to computational biologists beyond TAIR. As the technology proves itself, it can move beyond plant biology into the more general biological realm. Further information about this project may be found at the TAIR website: http://arabidopsis.org.