Generating protein three-dimensional fold signatures using inductive logic programming

M Turcotte , S.H Muggleton , M.J.E Sternberg
{"title":"Generating protein three-dimensional fold signatures using inductive logic programming","authors":"M Turcotte ,&nbsp;S.H Muggleton ,&nbsp;M.J.E Sternberg","doi":"10.1016/S0097-8485(01)00100-0","DOIUrl":null,"url":null,"abstract":"<div><p>Inductive logic programming (ILP) has been applied to automatically discover protein fold signatures. This paper investigates the use of topological information to circumvent problems encountered during previous experiments, namely (1) matching of non-structurally related secondary structures and (2) scaling problems. Cross-validation tests were carried out for 20 folds. The overall estimated accuracy is 73.37±0.35%. The new representation allows us to process the complete set of examples, while previously it was necessary to sample the negative examples. Topological information is used in approximately 90% of the rules presented here. Information about the topology of a sheet is present in 63% of the rules. This set of rules presents characteristics of the overall architecture of the fold. In contrast, 26% of the rules contain topological information which is limited to the packing of a restricted number of secondary structures, as such, the later set resembles those found in our previous studies.</p></div>","PeriodicalId":79331,"journal":{"name":"Computers & chemistry","volume":"26 1","pages":"Pages 57-64"},"PeriodicalIF":0.0000,"publicationDate":"2001-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0097-8485(01)00100-0","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & chemistry","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0097848501001000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Inductive logic programming (ILP) has been applied to automatically discover protein fold signatures. This paper investigates the use of topological information to circumvent problems encountered during previous experiments, namely (1) matching of non-structurally related secondary structures and (2) scaling problems. Cross-validation tests were carried out for 20 folds. The overall estimated accuracy is 73.37±0.35%. The new representation allows us to process the complete set of examples, while previously it was necessary to sample the negative examples. Topological information is used in approximately 90% of the rules presented here. Information about the topology of a sheet is present in 63% of the rules. This set of rules presents characteristics of the overall architecture of the fold. In contrast, 26% of the rules contain topological information which is limited to the packing of a restricted number of secondary structures, as such, the later set resembles those found in our previous studies.

利用归纳逻辑编程生成蛋白质三维折叠特征
归纳逻辑编程(ILP)已被应用于蛋白质折叠特征的自动发现。本文研究了利用拓扑信息来规避先前实验中遇到的问题,即(1)非结构相关二级结构的匹配问题和(2)缩放问题。对20个折叠进行交叉验证试验。总体估计精度为73.37±0.35%。新的表示允许我们处理完整的示例集,而以前必须对负示例进行采样。本文介绍的规则中大约90%使用了拓扑信息。关于工作表拓扑结构的信息出现在63%的规则中。这组规则呈现了褶皱整体架构的特征。相比之下,26%的规则包含拓扑信息,这些信息仅限于有限数量的二级结构的包装,因此,后一组类似于我们之前研究中发现的那些。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信