Suppr超能文献

对提交给CASP7结构域预测类别的预测结果的评估。

Assessment of predictions submitted for the CASP7 domain prediction category.

作者信息

Tress Michael, Cheng Jianlin, Baldi Pierre, Joo Keehyoung, Lee Jinwoo, Seo Joo-Hyun, Lee Jooyoung, Baker David, Chivian Dylan, Kim David, Ezkurdia Iakes

机构信息

Structural and Biological Computation Programme, Spanish National Cancer Research Centre, Madrid, Spain.

出版信息

Proteins. 2007;69 Suppl 8:137-51. doi: 10.1002/prot.21675.

Abstract

This paper details the assessment process and evaluation results for the Critical Assessment of Protein Structure Prediction (CASP7) domain prediction category. Domain predictions were assessed using the Normalized Domain Overlap score introduced in CASP6 and the accuracy of prediction of domain break points. The results of the analysis clearly demonstrate that the best methods are able to make consistently reliable predictions when the target has a structural template, although they are less good when the domain break occurs in a region not covered by a template. The conditions of the experiment meant that it was impossible to draw any conclusions about domain prediction for free modeling targets and it was also difficult to draw many distinctions between the best groups. Two thirds of the targets submitted were single domains and hence regarded as easy to predict. Even those targets defined as having multiple domains always had at least one domain with a similar template structure.

摘要

本文详细介绍了蛋白质结构预测关键评估(CASP7)结构域预测类别的评估过程和评估结果。使用CASP6中引入的标准化结构域重叠分数和结构域断点预测的准确性来评估结构域预测。分析结果清楚地表明,当目标具有结构模板时,最佳方法能够始终做出可靠的预测,尽管当结构域断点出现在模板未覆盖的区域时,效果会稍差。实验条件意味着无法对自由建模目标的结构域预测得出任何结论,并且也难以在最佳组之间做出许多区分。提交的目标中有三分之二是单结构域,因此被认为易于预测。即使那些被定义为具有多个结构域的目标,也总是至少有一个结构域具有相似的模板结构。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验