使用约束规划的顺式调节模块检测

Tias Guns, Hong Sun, K. Marchal, Siegfried Nijssen
{"title":"使用约束规划的顺式调节模块检测","authors":"Tias Guns, Hong Sun, K. Marchal, Siegfried Nijssen","doi":"10.1109/BIBM.2010.5706592","DOIUrl":null,"url":null,"abstract":"We propose a method for finding CRMs in a set of co-regulated genes. Each CRM consists of a set of binding sites of transcription factors. We wish to find CRMs involving the same transcription factors in multiple sequences. Finding such a combination of transcription factors is inherently a combinatorial problem. We solve this problem by combining the principles of itemset mining and constraint programming. The constraints involve the putative binding sites of transcription factors, the number of sequences in which they co-occur and the proximity of the binding sites. Genomic background sequences are used to assess the significance of the modules. We experimentally validate our approach and compare it with state-of-the-art techniques.","PeriodicalId":275098,"journal":{"name":"2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"415 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Cis-regulatory module detection using constraint programming\",\"authors\":\"Tias Guns, Hong Sun, K. Marchal, Siegfried Nijssen\",\"doi\":\"10.1109/BIBM.2010.5706592\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a method for finding CRMs in a set of co-regulated genes. Each CRM consists of a set of binding sites of transcription factors. We wish to find CRMs involving the same transcription factors in multiple sequences. Finding such a combination of transcription factors is inherently a combinatorial problem. We solve this problem by combining the principles of itemset mining and constraint programming. The constraints involve the putative binding sites of transcription factors, the number of sequences in which they co-occur and the proximity of the binding sites. Genomic background sequences are used to assess the significance of the modules. We experimentally validate our approach and compare it with state-of-the-art techniques.\",\"PeriodicalId\":275098,\"journal\":{\"name\":\"2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"volume\":\"415 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBM.2010.5706592\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2010.5706592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

我们提出了一种在一组共调控基因中寻找CRMs的方法。每个CRM由一组转录因子结合位点组成。我们希望在多个序列中找到涉及相同转录因子的crm。找到这样的转录因子组合本身就是一个组合问题。我们结合项目集挖掘和约束规划的原理来解决这个问题。这些限制包括转录因子的推定结合位点,它们共同发生的序列数量以及结合位点的接近性。基因组背景序列用于评估模块的重要性。我们通过实验验证了我们的方法,并将其与最先进的技术进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Cis-regulatory module detection using constraint programming
We propose a method for finding CRMs in a set of co-regulated genes. Each CRM consists of a set of binding sites of transcription factors. We wish to find CRMs involving the same transcription factors in multiple sequences. Finding such a combination of transcription factors is inherently a combinatorial problem. We solve this problem by combining the principles of itemset mining and constraint programming. The constraints involve the putative binding sites of transcription factors, the number of sequences in which they co-occur and the proximity of the binding sites. Genomic background sequences are used to assess the significance of the modules. We experimentally validate our approach and compare it with state-of-the-art techniques.
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
期刊最新文献
A gene ranking method using text-mining for the identification of disease related genes alns — A searchable and filterable sequence alignment format A fast and noise-adaptive rough-fuzzy hybrid algorithm for medical image segmentation An accurate, automatic method for markerless alignment of electron tomographic images Unsupervised integration of multiple protein disorder predictors
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1