[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-330404-105":59,"doc-detail-330404-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","deep-learning-to-decode-sites-of-rna-translation-in-normal-and-cancerous-tissues","Deep learning to decode sites of RNA translation in normal and cancerous tissues","","RNA translation is essential for cellular life and strongly influences human disease, yet reliably defining variation in translation remains a major analytical challenge. The work introduces RiboTIE, a transformer model that maps global RNA translation with unmatched precision and sensitivity for ribosome profiling data. Applying RiboTIE to normal brain and medulloblastoma samples provides high-resolution views of disease regulation, revealing how translation control differs in cancerous tissue.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/deep-learning-to-decode-sites-of-rna-translation-in-normal-and-cancerous-tissues/330404/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/deep-learning-to-decode-sites-of-rna-translation-in-normal-and-cancerous-tissues/330404.png","ImageObject",300,407,{"name":92,"@type":93},"Olivia Brown","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-04","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",12,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What is the main goal of the study?","Question",{"text":113,"@type":114},"To accurately map global RNA translation by decoding translation sites using a transformer model approach.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How does RiboTIE differ from prior Ribo-Seq analysis tools?",{"text":118,"@type":114},"It uses transformer-based learning to extract dataset-dependent correlations and scores candidate translation initiation sites across transcripts without requiring a pre-processing step.",{"name":120,"@type":111,"acceptedAnswer":121},"What data and inputs does RiboTIE rely on?",{"text":122,"@type":114},"It uses sequenced and mapped ribosome-protected fragments (RPFs) along transcripts and does not use DNA sequence information such as start codons or ORF characteristics.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},330404,1791398107,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":145,"read_time":146,"preview_page_count":4},16904993612988,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","bioRxiv preprint doi: [https://doi.org/10.1101/2024.03.21.586110](https://doi.org/10.1101/2024.03.21.586110); this version posted March 25, 2024. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made  \navailable under aCC-BY-ND 4.0 International license.  \nDeep learning to decode sites of RNA transla􀆟on in normal and cancerous 􀆟ssues  \nJim Clauwaert1-3,8, Zahra McVey4, Ramneek Gupta4, Ian Yannuzzi5, Gerben Menschaert6,7,8 & John R.  \nPrensner1-3,7,8  \nAffilia􀆟ons  \n1 Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, USA  \n2 Chad Carr Pediatric Brain Tumor Center, University of Michigan, Ann Arbor, MI, USA  \n3 Department of Biological Chemistry, University of Michigan, Ann Arbor, MI, USA  \n4 Novo Nordisk Research Centre Oxford, Novo Nordisk Ltd., Oxford, United Kingdom  \n5 Cancer Program, Broad Ins􀆟tute of MIT and Harvard, Cambridge, MA, USA  \n6 Department of Data Analysis and Mathema􀆟cal Modelling, Ghent University, Belgium  \n7 These authors share senior authorship: Gerben Menschaert, John R. Prensner  \n8 These authors are corresponding authors: Jim Clauwaert, Gerben Menschaert, John R. Prensner  \nKey words: Ribo-seq, non-canonical open reading frames, cancer, medulloblastoma, RNA transla􀆟on  \nAddress correspondence to:  \nJohn R. Prensner, MD, PhD  \nDepartment of Pediatrics and Biological Chemistry, University of Michigan  \nMedical Science Research Building II, Room 2560B  \n1150 Medical Center Drive  \nAnn Arbor, MI, 48109  \nEmail: [prensner@umich.edu](prensner@umich.edu)  \nPhone: 734-763-5939  \nJim Clauwaert, PhD  \nDepartment of Pediatrics and Biological Chemistry, University of Michigan  \nMedical Science Research Building II, Room 2560B  \n1150 Medical Center Drive  \nAnn Arbor, MI, 48109  \nEmail: [clauwaer@umich.edu](clauwaer@umich.edu)  \nPhone: 734-763-9031  \nGerben Menschaert, PhD  \nDepartment of Data Analysis and Mathema􀆟cal Modelling, Ghent University  \nCoupure Links 653  \n900 Gent, Belgium  \nEmail: gerben.menschaert@ugent.be  \nPhone: +32-926-49922  \nbioRxiv preprint doi: [https://doi.org/10.1101/2024.03.21.586110](https://doi.org/10.1101/2024.03.21.586110); this version posted March 25, 2024. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made  \navailable under aCC-BY-ND 4.0 International license.  \nAbstract  \nThe biological process of RNA transla􀆟on is fundamental to cellular life and has wide-ranging implica􀆟ons for human disease. Yet, accurately delinea􀆟ng the varia􀆟on in RNA transla􀆟on represents a significant challenge. Here, we develop RiboTIE, a transformer model-based approach to map global RNA transla􀆟on. We find that RiboTIE offers unparalleled precision and sensi􀆟vity for ribosome profiling data. Applica􀆟on of RiboTIE to normal brain and medulloblastoma cancer samples enables high-resolu􀆟on insights into disease regula􀆟on of RNA transla􀆟on.  \nWord count: 75  \nbioRxiv preprint doi: [https://doi.org/10.1101/2024.03.21.586110](https://doi.org/10.1101/2024.03.21.586110); this version posted March 25, 2024. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made  \navailable under aCC-BY-ND 4.0 International license.  \nMain  \nRNA transla􀆟on is an intricate process that involves the stepwise binding of the 40S and 60S ribosome subunits to RNA, along with mul􀆟ple eukaryo􀆟c ini􀆟a􀆟on factors and other cofactors.1 RNA transla􀆟on is a major determinant of protein abundance and represents a core area of disease biology including cancer, where numerous gene􀆟c and non-gene􀆟c factors alter the composi􀆟on of ribosomes, efficiency of transla􀆟on, and fidelity of transla􀆟on.2  \nTo gain global i","cbCaickL5ww1Xy1V","https://ap.wps.com/l/cbCaickL5ww1Xy1V","pdf",2787435,22,"English","# Abstract\n## RiboTIE transformer-based mapping approach\n## Global insights from ribosome profiling (Ribo-Seq)\n## Challenges and biases in Ribo-Seq analyses\n## Model features and interpretation","[{\"question\":\"What is the main goal of the study?\",\"answer\":\"To accurately map global RNA translation by decoding translation sites using a transformer model approach.\"},{\"question\":\"How does RiboTIE differ from prior Ribo-Seq analysis tools?\",\"answer\":\"It uses transformer-based learning to extract dataset-dependent correlations and scores candidate translation initiation sites across transcripts without requiring a pre-processing step.\"},{\"question\":\"What data and inputs does RiboTIE rely on?\",\"answer\":\"It uses sequenced and mapped ribosome-protected fragments (RPFs) along transcripts and does not use DNA sequence information such as start codons or ORF characteristics.\"}]","Deep learning to decode sites of RNA translation in normal and cancerous tissues | PDF",1789988656,55]