[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-352672-105":59,"doc-detail-352672-en":130},{"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":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","sicmir-atlas-single-cell-mirna-landscape-reveals-hub-mirna-and-network-signatures-in-human-cancers","SiCmiR Atlas: Single-Cell miRNA Landscape Reveals - Hub-miRNA and Network Signatures in Human Cancers","","MicroRNAs (miRNAs) are pivotal post‑transcriptional regulators whose single‑cell behavior has remained largely inaccessible due to technical barriers in single-cell small‑RNA profiling. SiCmiR presents a two‑layer neural network that predicts miRNA expression from 977 LINCS L1000 landmark genes to reduce dropout sensitivity in scRNA‑seq. Proof‑of‑concept analyses reveal candidate hub‑miRNAs across multiple cancer contexts. Trained on 6,462 TCGA paired miRNA–mRNA samples, SiCmiR reaches state‑of‑the‑art performance and generalizes to new cancer types and drug perturbations. SiCmiR‑Atlas further provides a dedicated single‑cell mature miRNA database with interactive visualization, biomarker discovery, and cell‑type‑resolved miRNA–target networks.",{"@graph":69,"@context":122},[70,84,105],{"@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/sicmir-atlas-single-cell-mirna-landscape-reveals-hub-mirna-and-network-signatures-in-human-cancers/352672/",{"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/sicmir-atlas-single-cell-mirna-landscape-reveals-hub-mirna-and-network-signatures-in-human-cancers/352672.png","ImageObject",300,407,{"name":92,"@type":93},"WPS_1786070896","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-23","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is SiCmiR and what problem does it address?","Question",{"text":112,"@type":113},"SiCmiR is a two-layer neural network designed to predict miRNA expression profiles from a limited set of landmark genes, addressing technical barriers and dropout sensitivity in single-cell small-RNA profiling and scRNA-seq.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does SiCmiR validate its ability to identify hub-miRNAs?",{"text":117,"@type":113},"The document reports proof-of-concept analyses showing SiCmiR can uncover candidate hub-miRNAs in several settings, including bulkseq cell lines and multiple cancer types using scRNA-seq.",{"name":119,"@type":110,"acceptedAnswer":120},"What does SiCmiR-Atlas provide beyond the prediction model?",{"text":121,"@type":113},"SiCmiR‑Atlas is a database that includes many public datasets and cells and enables interactive visualization, biomarker identification, and cell-type-resolved miRNA–target networks.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},352672,1790141818,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":14,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},549768072016,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Advanced Science    \n[www.advancedscience.com](www.advancedscience.com)  \n RESEARCH ARTICLE   \nSiCmiR Atlas: Single-Cell miRNA Landscape Reveals  \nHub-miRNA and Network Signatures in Human Cancers  \nXiao-Xuan Cai1, 2   Jing-Shan Liao2  Jia-Jun Ma2  Yu-Xuan Pang1  Yi-Gang Chen1, 2  Yang-Chi-Dung Lin1, 2, 3  Yi-Dan Chen1, 2  Xin Cao2  Yi-Cheng Zhang2  Tao-Sheng Xu1  Tzong-Yi Lee5  Hsi-Yuan Huang1, 2, 3   \nHsien-Da Huang1, 2, 3, 4  \n1Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, P. R. China   \n2 School of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, P. R. China  3 Guangdong Provincial Key Laboratory of Digital Biology and Drug Development, The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, P. R. China  4 Department of Endocrinology, Key Laboratory of Endocrinology of National Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union  \nMedical College, Beijing, P. R. China  5 Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan Correspondence: Hsi-Yuan Huang ([huanghsiyuan@cuhk.edu.cn](huanghsiyuan@cuhk.edu.cn))  Hsien-Da Huang (huanghsienda@cuhk.edu.cn)  \nReceived: 30 July 2025  Revised: 11 December 2025  Accepted: 20 December 2025  \nKeywords: atlas | biomarkers | cancers | hub-miRNA | miRNA | single-cell  \nABSTRACT  \nMicroRNAs (miRNAs) are pivotal post‑transcriptional regulators whose single‑cell behavior has remained largely inaccessible due to technical barriers in single-cell small‑RNA profiling. We present SiCmiR, a two‑layer neural network that predicts miRNA expression profiles from only 977 LINCS L1000 landmark genes, thereby reducing sensitivity to dropout in single-cell RNA-seq (scRNA-seq) data. Proof‑of‑concept analyses illustrate how SiCmiR can uncover candidate hub‑miRNAs in bulkseq cell lines and hepatocellular carcinoma, scRNA-seq pancreatic ductal carcinoma, and ACTH‑secreting pituitary adenoma and extracellular vesicle (EV)‑mediated crosstalk in glioblastoma. Trained on 6,462 TCGA paired miRNA–mRNA samples, SiCmiR attains state‑of‑the‑art accuracy on cancers and generalizes to unseen cancer types and drug perturbations. We next construct SiCmiR‑Atlas, containing 362 public datasets, 9.36 million cells, and 726 cell types, which is the first dedicated database of single‑cell mature miRNA expression, providing interactive visualization, biomarker identification, and cell‑type‑resolved miRNA–target networks. SiCmiR transforms bulk‑derived statistical power into a single‑cell view of miRNA biology and provides a community resource for biomarker discovery. SiCmiR Atlas is available at [https://awi.cuhk.edu.cn/](https://awi.cuhk.edu.cn/)∼SiCmiR/.  \n1  Introduction  \nMicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression. Most function as repressors by binding to the 3’-untranslated region (3’UTR) of mRNAs, initiating mRNA degradation and blocking translation, though certain miRNAshave been reported to stabilize mRNA and to enhance its activity [1]. Dysregulation of miRNAs and their protein translation in the regulatory network underpins virtually every cancer hallmark, such as proliferation, stemness, invasion, and immune evasion. MiRNAs are therefore valuable biomarkers and therapeutic tar-  \ngets [2] . MiRNAs that are strongly associated with mRNAs play central roles in the regulatory network, and are referred to as hubmiRNAs due to their significant impact [3]. As our understanding deepens, targeting these hub-miRNAs offers a promising frontier for advancing both cancer diagnostics and therapy.  \nAccording to the records of miRBase, 2656 mature miRNAshave been identified in humans [4], although not all have been assigned functional significance. This knowledge gap may be attributed to factors such as inadequate sample sizes, sequencing batch effects, and lim","cbCaia6MrfGXaRkD","https://ap.wps.com/l/cbCaia6MrfGXaRkD","pdf",7498072,17,"English","# Abstract\n# Introduction","[{\"question\":\"What is SiCmiR and what problem does it address?\",\"answer\":\"SiCmiR is a two-layer neural network designed to predict miRNA expression profiles from a limited set of landmark genes, addressing technical barriers and dropout sensitivity in single-cell small-RNA profiling and scRNA-seq.\"},{\"question\":\"How does SiCmiR validate its ability to identify hub-miRNAs?\",\"answer\":\"The document reports proof-of-concept analyses showing SiCmiR can uncover candidate hub-miRNAs in several settings, including bulkseq cell lines and multiple cancer types using scRNA-seq.\"},{\"question\":\"What does SiCmiR-Atlas provide beyond the prediction model?\",\"answer\":\"SiCmiR‑Atlas is a database that includes many public datasets and cells and enables interactive visualization, biomarker identification, and cell-type-resolved miRNA–target networks.\"}]","SiCmiR Atlas: Single-Cell miRNA Landscape Reveals - Hub-miRNA and Network Signatures in Human Cancers | PDF",1790100738,43]