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创建和维护专业蛋白质资源的主要挑战。

Key challenges for the creation and maintenance of specialist protein resources.

作者信息

Holliday Gemma L, Bairoch Amos, Bagos Pantelis G, Chatonnet Arnaud, Craik David J, Finn Robert D, Henrissat Bernard, Landsman David, Manning Gerard, Nagano Nozomi, O'Donovan Claire, Pruitt Kim D, Rawlings Neil D, Saier Milton, Sowdhamini Ramanathan, Spedding Michael, Srinivasan Narayanaswamy, Vriend Gert, Babbitt Patricia C, Bateman Alex

机构信息

Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, 94158.

SIB-Swiss Institute of Bioinformatics, University of Geneva, Geneva, Switzerland.

出版信息

Proteins. 2015 Jun;83(6):1005-13. doi: 10.1002/prot.24803. Epub 2015 Apr 22.

Abstract

As the volume of data relating to proteins increases, researchers rely more and more on the analysis of published data, thus increasing the importance of good access to these data that vary from the supplemental material of individual articles, all the way to major reference databases with professional staff and long-term funding. Specialist protein resources fill an important middle ground, providing interactive web interfaces to their databases for a focused topic or family of proteins, using specialized approaches that are not feasible in the major reference databases. Many are labors of love, run by a single lab with little or no dedicated funding and there are many challenges to building and maintaining them. This perspective arose from a meeting of several specialist protein resources and major reference databases held at the Wellcome Trust Genome Campus (Cambridge, UK) on August 11 and 12, 2014. During this meeting some common key challenges involved in creating and maintaining such resources were discussed, along with various approaches to address them. In laying out these challenges, we aim to inform users about how these issues impact our resources and illustrate ways in which our working together could enhance their accuracy, currency, and overall value.

摘要

随着与蛋白质相关的数据量不断增加,研究人员越来越依赖已发表数据的分析,因此能够良好获取这些数据变得愈发重要,这些数据涵盖从个别文章的补充材料到拥有专业人员和长期资金支持的主要参考数据库等各种类型。专业蛋白质资源填补了重要的中间地带,它们针对特定的蛋白质主题或家族,为其数据库提供交互式网络界面,采用在主要参考数据库中不可行的专门方法。许多此类资源是出于热爱而开展的工作,由单个实验室运营,几乎没有或完全没有专门的资金支持,而且构建和维护它们面临诸多挑战。这一观点源自2014年8月11日和12日在英国剑桥惠康信托基因组园区举行的一次由多个专业蛋白质资源和主要参考数据库参加的会议。在这次会议上,讨论了创建和维护此类资源所涉及的一些共同关键挑战以及应对这些挑战的各种方法。在阐述这些挑战时,我们旨在告知用户这些问题如何影响我们的资源,并说明我们共同合作可提高其准确性、时效性和整体价值的方式。

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Nucleic Acids Res. 2015 Jan;43(Database issue):D222-6. doi: 10.1093/nar/gku1221. Epub 2014 Nov 20.
3
Rfam 12.0: updates to the RNA families database.Rfam 12.0:RNA家族数据库的更新
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4
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6
The PDB_REDO server for macromolecular structure model optimization.PDB_REDO 服务器,用于大分子结构模型优化。
IUCrJ. 2014 May 30;1(Pt 4):213-20. doi: 10.1107/S2052252514009324. eCollection 2014 Jul 1.
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