[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119712-en":3,"doc-seo-119712-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119712,1099513958762,"Logic","https://ap-avatar.wpscdn.com/avatar/1000023916a998db790?x-image-process=image/resize,m_fixed,w_180,h_180&k=1784791008015729253",8,"Research & Report","Prediction of CTCF loop anchor based on machine learning","Chromatin loops contribute to the functional organization of the 3D genome, and CTCF acts as a key mammalian insulator whose genome-wide binding sites include only a subset that function as loop anchors. The study compares anchor versus non-anchor CTCF sites in terms of sequence preference and binding strength, then builds a machine learning model using CTCF binding intensity and DNA sequence features to predict anchor-forming sites. The model achieves 0.8646 accuracy, highlighting the roles of binding strength and binding patterns, supported by the CTCF core motif and flanking sequence.","TYPE Original Research PUBLISHED 03 April 2023  \nDOI 10.3389/fgene.2023.1181956  \nOPEN ACCESS  \nEDITED BY  \nNathan Olson,  \nNational Institute of Standards and Technology (NIST), United States  \nREVIEWED BY  \nZhibin Lv,  \nSichuan University, China Feifei Cui,  \nHainan University, China  \n*CORRESPONDENCE  \nWen Zhu,  \n [syzhuwen@163.com](syzhuwen@163.com)  \nSPECIALTY SECTION  \nThis article was submitted to Computational Genomics, a section of the journal Frontiers in Genetics  \nRECEIVED 08 March 2023  \nACCEPTED 24 March 2023  \nPUBLISHED 03 April 2023  \nCITATION  \nZhang X, Zhu W, Sun H, Ding Y and Liu L (2023), Prediction of CTCF loop anchor based on machine learning.  \nFront. Genet. 14:1181956 .  \ndoi: 10.3389/fgene.2023.1181956  \nCOPYRIGHT  \n© 2023 Zhang, Zhu, Sun, Ding and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nPrediction of CTCF loop anchor based on machine learning  \nXiao Zhang 1,2,3, Wen Zhu 1,3*, Huimin Sun 4, Yijie Ding 3 and Li Liu 2  \n1School of Mathematics and Statistics, Hainan Normal University, Haikou, China, 2Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China, 3Key Laboratory of Computational Science and Application of Hainan Province, Haikou, China, 4School of Physical Science and Technology, Inner Mongolia University, Hohhot, China  \nIntroduction: Various activities in biological cells are affected by threedimensional genome structure. The insulators play an important role in the organization of higher-order structure. CTCF is a representative of mammalian insulators, which can produce barriers to prevent the continuous extrusion of chromatin loop. As a multifunctional protein, CTCF has tens of thousands of binding sites in the genome, but only a portion of them can be used as anchors of chromatin loops. It is still unclear how cells select the anchor in the process of chromatin looping.  \nMethods: In this paper, a comparative analysis is performed to investigate the sequence preference and binding strength of anchor and non-anchor CTCF binding sites. Furthermore, a machine learning model based on the CTCF binding intensity and DNA sequence is proposed to predict which CTCF sites can form chromatin loop anchors.  \nResults: The accuracy of the machine learning model that we constructed for predicting the anchor of the chromatin loop mediated by CTCF reached 0 .8646. And we find that the formation of loop anchor is mainly influenced by the CTCF binding strength and binding pattern (which can be interpreted as the binding of different zinc fingers) .  \nDiscussion: In conclusion, our results suggest that The CTCF core motif and it’s flanking sequence may be responsible for the binding specificity. This work contributes to understanding the mechanism of loop anchor selection and provides a reference for the prediction of CTCF-mediated chromatin loops.  \nKEYWORDS  \nCTCF, Chromatin Loop, Machine Learning, DNA sequence, 3D Genome  \n1 Introduction  \nHigh-order chromatin structure influences a variety of biological processes in the nucleus, including gene transcription, gene regulation and DNA replication. The structure of interphase chromatin has been extensively researched with the development of various chromatin conformation capture techniques (Fullwood et al., 2009a; Fullwood et al., 2009b; Lieberman-Aiden et al., 2009; Hsieh et al., 2015), unveiling the functional units. For example, extensive researches on chromosome compartments (Dixon et al., 2012), topologically associated domains (TADs) (Rao et al., 2014) and loops (Narendra et al., 2015) have bee","cbCaim8HuUG1VE4c","https://ap.wps.com/l/cbCaim8HuUG1VE4c","pdf",1781027,1,10,"English","en",105,"# Introduction\n## CTCF and chromatin loop anchors\n## Genome organization and regulatory elements\n# Methods\n## Sequence preference and binding strength comparison\n## Machine learning model design\n# Results\n## Prediction accuracy and key influencing factors\n# Discussion\n## Core motif and flanking sequence implications\n## Contribution to loop anchor selection and prediction","[{\"question\":\"Why is predicting CTCF loop anchors important?\",\"answer\":\"Only a portion of CTCF binding sites serve as chromatin loop anchors, and the selection mechanism remains unclear. Predicting these anchors helps explain loop formation and improves understanding of CTCF-mediated genome organization.\"},{\"question\":\"What inputs does the proposed machine learning model use?\",\"answer\":\"The model uses CTCF binding intensity together with DNA sequence information to characterize anchor-forming versus non-anchor CTCF sites.\"},{\"question\":\"Which factors most influence loop anchor formation according to the results?\",\"answer\":\"Loop anchor formation is mainly influenced by CTCF binding strength and binding patterns, which relate to different zinc-finger binding behaviors.\"}]","Prediction of CTCF loop anchor based on machine learning | PDF",1785725915,25,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"prediction-of-ctcf-loop-anchor-based-on-machine-learning","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/prediction-of-ctcf-loop-anchor-based-on-machine-learning/119712/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is predicting CTCF loop anchors important?","Question",{"text":75,"@type":76},"Only a portion of CTCF binding sites serve as chromatin loop anchors, and the selection mechanism remains unclear. Predicting these anchors helps explain loop formation and improves understanding of CTCF-mediated genome organization.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What inputs does the proposed machine learning model use?",{"text":80,"@type":76},"The model uses CTCF binding intensity together with DNA sequence information to characterize anchor-forming versus non-anchor CTCF sites.",{"name":82,"@type":73,"acceptedAnswer":83},"Which factors most influence loop anchor formation according to the results?",{"text":84,"@type":76},"Loop anchor formation is mainly influenced by CTCF binding strength and binding patterns, which relate to different zinc-finger binding behaviors.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":21,"slug":133},"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]