PROMOCO:一个预测顺式调控元素的新程序:从高信息含量分析到集团识别

Guojun Li, Jizhu Lu, V. Olman, Ying Xu
{"title":"PROMOCO:一个预测顺式调控元素的新程序:从高信息含量分析到集团识别","authors":"Guojun Li, Jizhu Lu, V. Olman, Ying Xu","doi":"10.1109/CSBW.2005.113","DOIUrl":null,"url":null,"abstract":"We present a computational study for prediction of cis regulatory elements. We model the problem as follows. Each set of conserved binding motifs, evolved from one common ancestor, have a short (Hamming) distance from this ancestor. The problem is to identify a set of l-mers from a given set of promoter sequences which have at most k different positions from the to-be-identified ancestor. A number of papers published in the past attempt to solve this challenging problem. Although the putative ancestor is unknown, even it does not appear in whole background database, we may assume that an instance of it at hand since we can guess it. Our main contribution in this paper is to develop an algorithm, named PROMOCO (PROfile Motif Collection), to find a profile containing all the motifs and relatively small number of random l-mers so that the consensus of the profile would be the putative ancestor. The key idea of the PROMOCO algorithm lies in a new distance measure.","PeriodicalId":123531,"journal":{"name":"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"PROMOCO: a new program for prediction of cis regulatory elements: from high-information content analysis to clique identification\",\"authors\":\"Guojun Li, Jizhu Lu, V. Olman, Ying Xu\",\"doi\":\"10.1109/CSBW.2005.113\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a computational study for prediction of cis regulatory elements. We model the problem as follows. Each set of conserved binding motifs, evolved from one common ancestor, have a short (Hamming) distance from this ancestor. The problem is to identify a set of l-mers from a given set of promoter sequences which have at most k different positions from the to-be-identified ancestor. A number of papers published in the past attempt to solve this challenging problem. Although the putative ancestor is unknown, even it does not appear in whole background database, we may assume that an instance of it at hand since we can guess it. Our main contribution in this paper is to develop an algorithm, named PROMOCO (PROfile Motif Collection), to find a profile containing all the motifs and relatively small number of random l-mers so that the consensus of the profile would be the putative ancestor. The key idea of the PROMOCO algorithm lies in a new distance measure.\",\"PeriodicalId\":123531,\"journal\":{\"name\":\"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSBW.2005.113\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSBW.2005.113","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

我们提出了预测顺式调控元件的计算研究。我们对这个问题建模如下。每一组保守的结合基序,从一个共同的祖先进化而来,与这个祖先有很短的(汉明)距离。问题是从一组给定的启动子序列中识别一组l-mers,这些启动子序列与待识别的祖先最多有k个不同的位置。过去发表的一些论文试图解决这个具有挑战性的问题。虽然假定的祖先是未知的,即使它没有出现在整个后台数据库中,我们可以假设它的一个实例,因为我们可以猜测它。我们在本文中的主要贡献是开发了一种名为PROMOCO (PROfile Motif Collection)的算法,用于找到包含所有Motif和相对少量随机l-mers的PROfile,以便该PROfile的共识将是假定的祖先。PROMOCO算法的核心思想在于一种新的距离度量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PROMOCO: a new program for prediction of cis regulatory elements: from high-information content analysis to clique identification
We present a computational study for prediction of cis regulatory elements. We model the problem as follows. Each set of conserved binding motifs, evolved from one common ancestor, have a short (Hamming) distance from this ancestor. The problem is to identify a set of l-mers from a given set of promoter sequences which have at most k different positions from the to-be-identified ancestor. A number of papers published in the past attempt to solve this challenging problem. Although the putative ancestor is unknown, even it does not appear in whole background database, we may assume that an instance of it at hand since we can guess it. Our main contribution in this paper is to develop an algorithm, named PROMOCO (PROfile Motif Collection), to find a profile containing all the motifs and relatively small number of random l-mers so that the consensus of the profile would be the putative ancestor. The key idea of the PROMOCO algorithm lies in a new distance measure.
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:604180095
Book学术官方微信