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脊柱生物信息学与高通量结构生物学的数据管理方面。

SPINE bioinformatics and data-management aspects of high-throughput structural biology.

作者信息

Albeck S, Alzari P, Andreini C, Banci L, Berry I M, Bertini I, Cambillau C, Canard B, Carter L, Cohen S X, Diprose J M, Dym O, Esnouf R M, Felder C, Ferron F, Guillemot F, Hamer R, Ben Jelloul M, Laskowski R A, Laurent T, Longhi S, Lopez R, Luchinat C, Malet H, Mochel T, Morris R J, Moulinier L, Oinn T, Pajon A, Peleg Y, Perrakis A, Poch O, Prilusky J, Rachedi A, Ripp R, Rosato A, Silman I, Stuart D I, Sussman J L, Thierry J C, Thompson J D, Thornton J M, Unger T, Vaughan B, Vranken W, Watson J D, Whamond G, Henrick K

机构信息

The Israel Proteomics Center, The Department of Structural Biology, The Weizmann Institute of Science, Rehovot, Israel.

出版信息

Acta Crystallogr D Biol Crystallogr. 2006 Oct;62(Pt 10):1184-95. doi: 10.1107/S090744490602991X. Epub 2006 Sep 19.

Abstract

SPINE (Structural Proteomics In Europe) was established in 2002 as an integrated research project to develop new methods and technologies for high-throughput structural biology. Development areas were broken down into workpackages and this article gives an overview of ongoing activity in the bioinformatics workpackage. Developments cover target selection, target registration, wet and dry laboratory data management and structure annotation as they pertain to high-throughput studies. Some individual projects and developments are discussed in detail, while those that are covered elsewhere in this issue are treated more briefly. In particular, this overview focuses on the infrastructure of the software that allows the experimentalist to move projects through different areas that are crucial to high-throughput studies, leading to the collation of large data sets which are managed and eventually archived and/or deposited.

摘要

欧洲结构蛋白质组学(SPINE)成立于2002年,是一个综合研究项目,旨在开发高通量结构生物学的新方法和技术。开发领域被细分为多个工作包,本文概述了生物信息学工作包的当前活动。开发内容涵盖与高通量研究相关的靶标选择、靶标登记、湿实验室和干实验室数据管理以及结构注释。详细讨论了一些个别项目和开发情况,而本期其他地方涵盖的内容则处理得较为简略。特别是,本概述重点关注软件基础设施,该设施使实验人员能够在对高通量研究至关重要的不同领域推进项目,从而整理出经过管理并最终存档和/或存放的大型数据集。

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