Information theoretic clustering of the human pangenome minigraph

IF 3.9 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Renato Ferrero , Filippo Gandino , Anna Carbone
{"title":"Information theoretic clustering of the human pangenome minigraph","authors":"Renato Ferrero ,&nbsp;Filippo Gandino ,&nbsp;Anna Carbone","doi":"10.1016/j.patrec.2025.03.004","DOIUrl":null,"url":null,"abstract":"<div><div>Information theoretic clustering, long-range correlation, power-law scaling and self-similarity concepts have been broadly adopted for characterizing genomic features such as nucleotide composition, flexibility and bending. In this work, the 24 chromosomes of the human pangenome minigraphs, recently assembled by the Human Pangenome Reference Consortium (HPRC), are investigated to check to what extent self-similarity and scaling features are preserved in comparison to the reference linear sequences of the T2T-CHM13 individual. By taking the nucleotide self-similarity of the reference chromosomes as benchmark, it is shown that the pangenome minigraph segments exhibit lower self-similarity of the nucleotide composition compared to the linear sequence. The proposed information measures can be adopted to quantify the nucleotide self-similarity patterns and complement standard alignment techniques towards the coherent definition of the genomic profile of each species.</div></div>","PeriodicalId":54638,"journal":{"name":"Pattern Recognition Letters","volume":"191 ","pages":"Pages 117-123"},"PeriodicalIF":3.9000,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pattern Recognition Letters","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167865525000881","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

Information theoretic clustering, long-range correlation, power-law scaling and self-similarity concepts have been broadly adopted for characterizing genomic features such as nucleotide composition, flexibility and bending. In this work, the 24 chromosomes of the human pangenome minigraphs, recently assembled by the Human Pangenome Reference Consortium (HPRC), are investigated to check to what extent self-similarity and scaling features are preserved in comparison to the reference linear sequences of the T2T-CHM13 individual. By taking the nucleotide self-similarity of the reference chromosomes as benchmark, it is shown that the pangenome minigraph segments exhibit lower self-similarity of the nucleotide composition compared to the linear sequence. The proposed information measures can be adopted to quantify the nucleotide self-similarity patterns and complement standard alignment techniques towards the coherent definition of the genomic profile of each species.
求助全文
约1分钟内获得全文 求助全文
来源期刊
Pattern Recognition Letters
Pattern Recognition Letters 工程技术-计算机:人工智能
CiteScore
12.40
自引率
5.90%
发文量
287
审稿时长
9.1 months
期刊介绍: Pattern Recognition Letters aims at rapid publication of concise articles of a broad interest in pattern recognition. Subject areas include all the current fields of interest represented by the Technical Committees of the International Association of Pattern Recognition, and other developing themes involving learning and recognition.
×
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