PQL:蛋白质查询语言

S. Elfayoumy, Paul Bathen
{"title":"PQL:蛋白质查询语言","authors":"S. Elfayoumy, Paul Bathen","doi":"10.1109/ICMLA.2012.217","DOIUrl":null,"url":null,"abstract":"This paper introduces a Protein Query Language (PQL) for querying protein structures in an expressive yet concise manner. One of the objectives of the paper is to demonstrate how such a language would be beneficial to protein researchers to obtain in-depth protein data from a relational database without extensive SQL knowledge. The language features options such as limiting query results by key protein characteristics such as methyl donated hydrogen bond interactions, minimum and maximum phi and psi angles, repulsive forces, CH/Pi calculations, and other pertinent factors. A backend data model was designed to support storage and retrieval of protein primary and secondary sequences, atomic-level data, as well as calculations on said data. A relational DBMS is used as the persistent storage backend, with every effort made to ensure transparent portability to most relational database systems. In addition, front end applications can be developed to support retrieving, transforming, and preprocessing of information from the Research Collaboratory for Structural Bioinformatics (RCSB) into the backend data repository. The new language and associated architecture allow users to load additional protein files from RCSB into the database, issue standard queries to download pertinent data in user-friendly formats including CSV files, issue non-standard queries against secondary structures via the protein query language, and run error-detection routines against data in the database. Query results may include normalized or denormalized data, model and chain data, residue data, atom detail data, and primary as well as secondary structure data.","PeriodicalId":157399,"journal":{"name":"2012 11th International Conference on Machine Learning and Applications","volume":"321 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PQL: Protein Query Language\",\"authors\":\"S. Elfayoumy, Paul Bathen\",\"doi\":\"10.1109/ICMLA.2012.217\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a Protein Query Language (PQL) for querying protein structures in an expressive yet concise manner. One of the objectives of the paper is to demonstrate how such a language would be beneficial to protein researchers to obtain in-depth protein data from a relational database without extensive SQL knowledge. The language features options such as limiting query results by key protein characteristics such as methyl donated hydrogen bond interactions, minimum and maximum phi and psi angles, repulsive forces, CH/Pi calculations, and other pertinent factors. A backend data model was designed to support storage and retrieval of protein primary and secondary sequences, atomic-level data, as well as calculations on said data. A relational DBMS is used as the persistent storage backend, with every effort made to ensure transparent portability to most relational database systems. In addition, front end applications can be developed to support retrieving, transforming, and preprocessing of information from the Research Collaboratory for Structural Bioinformatics (RCSB) into the backend data repository. The new language and associated architecture allow users to load additional protein files from RCSB into the database, issue standard queries to download pertinent data in user-friendly formats including CSV files, issue non-standard queries against secondary structures via the protein query language, and run error-detection routines against data in the database. Query results may include normalized or denormalized data, model and chain data, residue data, atom detail data, and primary as well as secondary structure data.\",\"PeriodicalId\":157399,\"journal\":{\"name\":\"2012 11th International Conference on Machine Learning and Applications\",\"volume\":\"321 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 11th International Conference on Machine Learning and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLA.2012.217\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 11th International Conference on Machine Learning and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLA.2012.217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文介绍了一种蛋白质查询语言(PQL),用于以一种简洁而富有表现力的方式查询蛋白质结构。本文的目标之一是演示这种语言如何有助于蛋白质研究人员从关系数据库中获得深入的蛋白质数据,而无需广泛的SQL知识。该语言的功能选项包括通过关键蛋白质特征(如甲基捐赠氢键相互作用、最小和最大phi和psi角、排异力、CH/Pi计算和其他相关因素)限制查询结果。设计了一个后端数据模型,以支持蛋白质一级和二级序列的存储和检索、原子级数据以及对这些数据的计算。关系DBMS用作持久存储后端,并尽一切努力确保对大多数关系数据库系统的透明可移植性。此外,可以开发前端应用程序来支持从结构生物信息学研究合作实验室(RCSB)到后端数据存储库的信息检索、转换和预处理。新语言和相关架构允许用户从RCSB加载额外的蛋白质文件到数据库中,发出标准查询以用户友好格式下载相关数据,包括CSV文件,通过蛋白质查询语言对二级结构发出非标准查询,并对数据库中的数据运行错误检测例程。查询结果可能包括规范化或非规范化的数据、模型和链数据、剩余数据、原子细节数据以及主要和次要结构数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PQL: Protein Query Language
This paper introduces a Protein Query Language (PQL) for querying protein structures in an expressive yet concise manner. One of the objectives of the paper is to demonstrate how such a language would be beneficial to protein researchers to obtain in-depth protein data from a relational database without extensive SQL knowledge. The language features options such as limiting query results by key protein characteristics such as methyl donated hydrogen bond interactions, minimum and maximum phi and psi angles, repulsive forces, CH/Pi calculations, and other pertinent factors. A backend data model was designed to support storage and retrieval of protein primary and secondary sequences, atomic-level data, as well as calculations on said data. A relational DBMS is used as the persistent storage backend, with every effort made to ensure transparent portability to most relational database systems. In addition, front end applications can be developed to support retrieving, transforming, and preprocessing of information from the Research Collaboratory for Structural Bioinformatics (RCSB) into the backend data repository. The new language and associated architecture allow users to load additional protein files from RCSB into the database, issue standard queries to download pertinent data in user-friendly formats including CSV files, issue non-standard queries against secondary structures via the protein query language, and run error-detection routines against data in the database. Query results may include normalized or denormalized data, model and chain data, residue data, atom detail data, and primary as well as secondary structure data.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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:481959085
Book学术官方微信