Data to knowledge: how to get meaning from your result

被引:10
作者
Berman, Helen M. [1 ]
Gabanyi, Margaret J. [1 ]
Groom, Colin R. [2 ]
Johnson, John E. [3 ]
Murshudov, Garib N. [4 ]
Nicholls, Robert A. [4 ]
Reddy, Vijay [3 ]
Schwede, Torsten [5 ,6 ]
Zimmerman, Matthew D. [7 ]
Westbrook, John [1 ]
Minor, Wladek [7 ]
机构
[1] Rutgers State Univ, Dept Chem & Chem Biol, Ctr Integrat Prote Res, Piscataway, NJ 08854 USA
[2] Cambridge Crystallog Data Ctr, Cambridge CB2 1EZ, England
[3] Scripps Res Inst, Dept Integrat Struct & Computat Biol, La Jolla, CA 92037 USA
[4] MRC, Mol Biol Lab, Cambridge CB2 0QH, England
[5] Univ Basel, Biozentrum, CH-4056 Basel, Switzerland
[6] SIB Swiss Inst Bioinformat, Basel, Switzerland
[7] Univ Virginia, Dept Mol Physiol & Biol Phys, Charlottesville, VA 22908 USA
来源
IUCRJ | 2015年 / 2卷
基金
美国国家卫生研究院;
关键词
meaning from data; big data; data bases; knowledge bases; data deposition; PROTEIN-STRUCTURE PREDICTION; MODEL QUALITY ASSESSMENT; STRUCTURAL BIOLOGY KNOWLEDGEBASE; CRYSTAL-STRUCTURE PREDICTION; 5TH BLIND TEST; N-OMEGA-V; X-RAY; LARGE-SCALE; RNA VIRUS; BIOMEDICAL-RESEARCH;
D O I
10.1107/S2052252514023306
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Structural and functional studies require the development of sophisticated 'Big Data' technologies and software to increase the knowledge derived and ensure reproducibility of the data. This paper presents summaries of the Structural Biology Knowledge Base, the VIPERdb Virus Structure Database, evaluation of homology modeling by the Protein Model Portal, the ProSMART tool for conformation- independent structure comparison, the LabDB 'super' laboratory information management system and the Cambridge Structural Database. These techniques and technologies represent important tools for the transformation of crystallographic data into knowledge and information, in an effort to address the problem of non-reproducibility of experimental results.
引用
收藏
页码:45 / 58
页数:14
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