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Web and Grid Technologies in Bioinformatics, Computational and Systems Biology: A Review

机译:生物信息学,计算和系统生物学中的Web和网格技术:综述

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The acquisition of biological data, ranging from molecular characterization and simulations (e.g. protein folding dynamics), to systems biology endeavors (e.g. whole organ simulations) all the way up to ecological observations (e.g. as to ascertain climate change's impact on the biota) is growing at unprecedented speed. The use of computational and networking resources is thus unavoidable. As the datasets become bigger and the acquisition technology more refined, the biologist is empowered to ask deeper and more complex questions. These, in turn, drive a runoff effect where large research consortia emerge that span beyond organizations and national boundaries. Thus the need for reliable, robust, certified, curated, accessible, secure and timely data processing and management becomes entrenched within, and crucial to, 21st century biology. Furthermore, the proliferation of biotechnologies and advances in biological sciences has produced a strong drive for new informatics solutions, both at the basic science and technological levels. The previously unknown situation of dealing with, on one hand, (potentially) exabytes of data, much of which is noisy, has large experimental errors or theoretical uncertainties associated with it, or on the other hand, large quantities of data that require automated computationally intense analysis and processing, have produced important innovations in web and grid technology. In this paper we present a trace of these technological changes in Web and Grid technology, including details of emerging infrastructures, standards, languages and tools, as they apply to bioinformatics, computational biology and systems biology. A major focus of this technological review is to collate up-to-date information regarding the design and implementation of various bioinformatics Webs, Grids, Web-based grids or Grid-based webs in terms of their infrastructure, standards, protocols, services, applications and other tools. This review, besides surveying the current state-of-the-art, will also provide a road map for future research and open questions.
机译:从分子表征和模拟(例如蛋白质折叠动力学)到系统生物学努力(例如整个器官模拟)一直到生态观测(例如确定气候变化对生物群的影响)的生物数据的获取正在增长。以前所未有的速度因此,不可避免地要使用计算和网络资源。随着数据集的不断扩大和采集技术的不断完善,生物学家有权提出更深,更复杂的问题。这些反过来又导致了径流效应,在这种效应下,出现了跨越组织和国界的大型研究财团。因此,对可靠,可靠,经过认证,可管理,可访问,安全且及时的数据处理和管理的需求已根深蒂固,并且对于21世纪生物学至关重要。此外,生物技术的普及和生物科学的发展为基础科学和技术层面的新信息学解决方案提供了强大的动力。一方面(可能)处理数十亿字节的数据(其中很多是嘈杂的),这种先前未知的情况具有较大的实验误差或与之相关的理论不确定性,另一方面,大量的数据需要自动计算密集的分析和处理,已经在Web和网格技术方面产生了重要的创新。在本文中,我们介绍了Web和Grid技术中这些技术变化的踪迹,包括新兴基础设施,标准,语言和工具的详细信息,这些新技术适用于生物信息学,计算生物学和系统生物学。这项技术审查的主要重点是整理有关各种生物信息学Web,网格,基于Web的网格或基于Grid的Web的基础结构,标准,协议,服务,应用程序的设计和实现的最新信息。和其他工具。除了对当前的最新技术进行调查之外,这篇评论还将为将来的研究和未解决的问题提供一个路线图。

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