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学科主题物理化学
A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites
Xu, Beisi1,2,3; Schones, Dustin E.4; Wang, Yongmei5; Liang, Haojun6; Li, Guohui1; Li GH(李国辉)
刊名PLOS ONE
2013-01-08
ISSN1932-6203
DOI10.1371/journal.pone.0052460
8期:1页:52460
收录类别SCI
合作性质
文章类型Article
部门归属11
项目归属1106
产权排名待补充
WOS标题词Science & Technology
资助者1,1 ; 1,1 ; 1,1 ; 1,1
类目[WOS]Multidisciplinary Sciences
研究领域[WOS]Science & Technology - Other Topics
关键词[WOS]PROTEIN-DNA INTERACTIONS ; STRUCTURE-BASED PREDICTION ; SACCHAROMYCES-CEREVISIAE ; ENERGY FUNCTION ; ALL-ATOM ; REGULATORY PROTEINS ; TARGET SITES ; SPECIFICITY ; COMPLEXES ; PROFILES
英文摘要Scanning through genomes for potential transcription factor binding sites (TFBSs) is becoming increasingly important in this post-genomic era. The position weight matrix (PWM) is the standard representation of TFBSs utilized when scanning through sequences for potential binding sites. However, many transcription factor (TF) motifs are short and highly degenerate, and methods utilizing PWMs to scan for sites are plagued by false positives. Furthermore, many important TFs do not have well-characterized PWMs, making identification of potential binding sites even more difficult. One approach to the identification of sites for these TFs has been to use the 3D structure of the TF to predict the DNA structure around the TF and then to generate a PWM from the predicted 3D complex structure. However, this approach is dependent on the similarity of the predicted structure to the native structure. We introduce here a novel approach to identify TFBSs utilizing structure information that can be applied to TFs without characterized PWMs, as long as a 3D complex structure (TF/DNA) exists. This approach utilizes an energy function that is uniquely trained on each structure. Our approach leads to increased prediction accuracy and robustness compared with those using a more general energy function. The software is freely available upon request.
语种英语
资助者1,1 ; 1,1 ; 1,1 ; 1,1
原文出处查看原文
WOS记录号WOS:000313429800015
引用统计
被引频次:16[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://cas-ir.dicp.ac.cn/handle/321008/119639
专题中国科学院大连化学物理研究所
通讯作者Li GH(李国辉)
作者单位1.Chinese Acad Sci, Dalian Inst Chem Phys, State Key Lab Mol React Dynam, Lab Mol Modeling & Design, Dalian, Liaoning, Peoples R China
2.Univ Tennessee, Ctr Hlth Sci, Dept Microbiol Immunol & Biochem, Memphis, TN 38163 USA
3.Univ Tennessee, Ctr Hlth Sci, Ctr Integrat & Translat Gen, Memphis, TN 38163 USA
4.City Hope Natl Med Ctr, Beckman Res Inst, Dept Canc Biol, Duarte, CA 91010 USA
5.Univ Memphis, Dept Chem, Memphis, TN 38152 USA
6.Univ Sci & Technol China, Dept Polymer Sci & Engn, Hefei, Anhui, Peoples R China
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GB/T 7714
Xu, Beisi,Schones, Dustin E.,Wang, Yongmei,et al. A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites[J]. PLOS ONE,2013,8(1):52460.
APA Xu, Beisi,Schones, Dustin E.,Wang, Yongmei,Liang, Haojun,Li, Guohui,&李国辉.(2013).A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites.PLOS ONE,8(1),52460.
MLA Xu, Beisi,et al."A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites".PLOS ONE 8.1(2013):52460.
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