{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T05:09:59Z","timestamp":1788930599003,"version":"build-2803163510"},"reference-count":75,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32100515"],"award-info":[{"award-number":["32100515"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004853","name":"Chinese University of Hong Kong","doi-asserted-by":"publisher","award":["2021.061"],"award-info":[{"award-number":["2021.061"]}],"id":[{"id":"10.13039\/501100004853","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004853","name":"Chinese University of Hong Kong","doi-asserted-by":"publisher","award":["2022.080"],"award-info":[{"award-number":["2022.080"]}],"id":[{"id":"10.13039\/501100004853","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["U54AG079758"],"award-info":[{"award-number":["U54AG079758"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["R01AG085498"],"award-info":[{"award-number":["R01AG085498"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["P30CA030199"],"award-info":[{"award-number":["P30CA030199"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["R01CA287114"],"award-info":[{"award-number":["R01CA287114"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["R21GM159319"],"award-info":[{"award-number":["R21GM159319"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"National Heart, Lung, and Blood Institute","doi-asserted-by":"publisher","award":["R21HL177724"],"award-info":[{"award-number":["R21HL177724"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001368","name":"V Foundation for Cancer Research","doi-asserted-by":"publisher","award":["V2025\u2010028"],"award-info":[{"award-number":["V2025\u2010028"]}],"id":[{"id":"10.13039\/100001368","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Science"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Computational enhancement is an important strategy for inferring high\u2010resolution features from genome\u2010wide chromosome conformation capture (Hi\u2010C) data, which typically have limited resolution. Deep learning has been highly successful in this task but we show that it creates prevalent artificial structures in the enhanced data due to the need to divide the large contact matrix into small patches. In addition, previous deep learning methods largely focus on local patterns, which cannot fully capture the complexity of Hi\u2010C data. Here we propose Smooth, High\u2010resolution, and Accurate Reconstruction of Patterns (SHARP) for enhancing Hi\u2010C data. It uses the novel approach of decomposing the data into three types of signals, due to one\u2010dimensional proximity, contiguous domains, and other fine structures, respectively, and applies deep learning only to the third type of signals, such that enhancement of the first two is unaffected by the patches. For the deep learning part, SHARP uses both local and global attention mechanisms to capture multi\u2010scale contextual information. We compare SHARP with state\u2010of\u2010the\u2010art methods extensively, including application to data from new samples and another species, and show that SHARP has superior performance in terms of resolution enhancement accuracy, avoiding creation of artificial structures, identifying significant interactions, and enrichment in chromatin\u00a0states.<\/jats:p>","DOI":"10.1002\/advs.202524180","type":"journal-article","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T04:49:05Z","timestamp":1788929345000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Overcoming Artificial Structures in Resolution\u2010Enhanced Hi\u2010C Data by Signal Decomposition and Multi\u2010Scale Attention"],"prefix":"10.1002","author":[{"given":"Qinyao","family":"Li","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering The Chinese University of Hong Kong New Territories Hong Kong SAR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kelly Yichen","family":"Li","sequence":"additional","affiliation":[{"name":"Center for Data Science and Artificial Intelligence Sanford Burnham Prebys Medical Discovery Institute La Jolla California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chiara","family":"Nicoletti","sequence":"additional","affiliation":[{"name":"Center for Data Science and Artificial Intelligence Sanford Burnham Prebys Medical Discovery Institute La Jolla California USA"},{"name":"Center for Cardiovascular and Muscular Diseases Sanford Burnham Prebys Medical Discovery Institute La Jolla California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen Kwok\u2010Wing","family":"Tsui","sequence":"additional","affiliation":[{"name":"School of Biomedical Sciences The Chinese University of Hong Kong New Territories Hong Kong SAR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pier Lorenzo","family":"Puri","sequence":"additional","affiliation":[{"name":"Center for Data Science and Artificial Intelligence Sanford Burnham Prebys Medical Discovery Institute La Jolla California USA"},{"name":"Center for Cardiovascular and Muscular Diseases Sanford Burnham Prebys Medical Discovery Institute La Jolla California USA"},{"name":"Cancer Genome and Epigenetics Program, NCI\u2010Designated Cancer Center Sanford Burnham Prebys Medical Discovery Institute La Jolla California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qin","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Biomedical Sciences The Chinese University of Hong Kong New Territories Hong Kong SAR China"},{"name":"Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin Y.","family":"Yip","sequence":"additional","affiliation":[{"name":"Center for Data Science and Artificial Intelligence Sanford Burnham Prebys Medical Discovery Institute La Jolla California USA"},{"name":"Cancer Genome and Epigenetics Program, NCI\u2010Designated Cancer Center Sanford Burnham Prebys Medical Discovery Institute La Jolla California USA"},{"name":"Center for Neurologic Diseases Sanford Burnham Prebys Medical Discovery Institute La Jolla California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,8]]},"reference":[{"issue":"4","key":"e_1_2_9_2_1","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1038\/nrm3965","article-title":"Three\u2010Dimensional Genome Architecture: Players And Mechanisms","volume":"16","author":"Pombo A.","year":"2015","journal-title":"Nature Reviews Molecular Cell Biology"},{"issue":"7671","key":"e_1_2_9_3_1","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1038\/nature23884","article-title":"The 4D Nucleome Project","volume":"549","author":"Dekker J.","year":"2017","journal-title":"Nature"},{"issue":"7","key":"e_1_2_9_4_1","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1038\/s41576-018-0007-0","article-title":"Structural Variation In The 3D Genome","volume":"19","author":"Spielmann M.","year":"2018","journal-title":"Nature Reviews Genetics"},{"issue":"5871","key":"e_1_2_9_5_1","doi-asserted-by":"crossref","first-page":"1793","DOI":"10.1126\/science.1152850","article-title":"Gene Regulation In The Third Dimension","volume":"319","author":"Dekker J.","year":"2008","journal-title":"Science"},{"issue":"2","key":"e_1_2_9_6_1","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/S0959-437X(00)00169-6","article-title":"Higher\u2010Order Structure Of Chromatin And Chromosomes","volume":"11","author":"Woodcock C. L.","year":"2001","journal-title":"Current Opinion in Genetics and Development"},{"issue":"5950","key":"e_1_2_9_7_1","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1126\/science.1181369","article-title":"Comprehensive Mapping Of Long\u2010Range Interactions Reveals Folding Principles Of The Human Genome","volume":"326","author":"Lieberman\u2010Aiden E.","year":"2009","journal-title":"Science"},{"issue":"7","key":"e_1_2_9_8_1","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.1016\/j.cell.2014.11.021","article-title":"A 3D Map Of The Human Genome At Kilobase Resolution Reveals Principles Of Chromatin Looping","volume":"159","author":"Rao S. S. P.","year":"2014","journal-title":"Cell"},{"issue":"1","key":"e_1_2_9_9_1","first-page":"1","article-title":"Enhancing Hi\u2010C Data Resolution With Deep Convolutional Neural Network Hicplus","volume":"9","author":"Zhang Y.","year":"2018","journal-title":"Nature Communications"},{"issue":"2","key":"e_1_2_9_10_1","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.ajhg.2021.01.009","article-title":"Hic\u2010Act: Improved Detection Of Chromatin Interactions From Hi\u2010C Data Via Aggregated Cauchy Test","volume":"108","author":"Lagler T. M.","year":"2021","journal-title":"The American Journal of Human Genetics"},{"issue":"1","key":"e_1_2_9_11_1","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1186\/s13072-021-00417-4","article-title":"Seeing The Forest Through The Trees: Prioritising Potentially Functional Interactions From Hi\u2010C","volume":"14","author":"Liu N.","year":"2021","journal-title":"Epigenetics and Chromatin"},{"issue":"12","key":"e_1_2_9_12_1","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1038\/nrm.2016.104","article-title":"Genome\u2010Wide Mapping And Analysis Of Chromosome Architecture","volume":"17","author":"Schmitt A. D.","year":"2016","journal-title":"Nature Reviews Molecular Cell Biology"},{"issue":"7475","key":"e_1_2_9_13_1","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1038\/nature12644","article-title":"A High\u2010Resolution Map Of The Three\u2010Dimensional Chromatin Interactome In Human Cells","volume":"503","author":"Jin F.","year":"2013","journal-title":"Nature"},{"issue":"5","key":"e_1_2_9_14_1","doi-asserted-by":"crossref","first-page":"1369","DOI":"10.1016\/j.cell.2016.09.037","article-title":"Lineage\u2010Specific Genome Architecture Links Enhancers And Non\u2010Coding Disease Variants To Target Gene Promoters","volume":"167","author":"Javierre B. M.","year":"2016","journal-title":"Cell"},{"key":"e_1_2_9_15_1","first-page":"1","article-title":"High\u2010Resolution Hi\u2010C Maps Highlight Multiscale 3D Epigenome Reprogramming During Pancreatic Cancer Metastasis","volume":"14","author":"Ren B.","year":"2021","journal-title":"Journal of Hematology and Oncology"},{"issue":"1","key":"e_1_2_9_16_1","doi-asserted-by":"crossref","first-page":"5827","DOI":"10.1038\/s41467-022-33427-1","article-title":"High\u2010Resolution Genome Topology Of Human Retina Uncovers Super Enhancer\u2010Promoter Interactions At Tissue\u2010Specific And Multifactorial Disease Loci","volume":"13","author":"Marchal C.","year":"2022","journal-title":"Nature Communications"},{"issue":"14","key":"e_1_2_9_17_1","doi-asserted-by":"crossref","first-page":"i99","DOI":"10.1093\/bioinformatics\/btz317","article-title":"hicGAN Infers Super Resolution Hi\u2010C Data With Generative Adversarial Networks","volume":"35","author":"Liu Q.","year":"2019","journal-title":"Bioinformatics"},{"issue":"21","key":"e_1_2_9_18_1","doi-asserted-by":"crossref","first-page":"4222","DOI":"10.1093\/bioinformatics\/btz251","article-title":"HiCNN: A Very Deep Convolutional Neural Network To Better Enhance The Resolution Of Hi\u2010C Data","volume":"35","author":"Liu T.","year":"2019","journal-title":"Bioinformatics"},{"key":"e_1_2_9_19_1","doi-asserted-by":"crossref","unstructured":"M.Dimmick HiCSR: A Hi\u2010C Super\u2010Resolution Framework for Producing Highly Realistic Contact Maps PhD thesis(University of Toronto 2020).","DOI":"10.1101\/2020.02.24.961714"},{"key":"e_1_2_9_20_1","doi-asserted-by":"crossref","first-page":"2414","DOI":"10.1093\/bioinformatics\/btac156","article-title":"HiCARN: Resolution Enhancement Of Hi\u2010C Data Using Cascading Residual Networks","volume":"38","author":"Hicks P.","year":"2022","journal-title":"Bioinformatics"},{"key":"e_1_2_9_21_1","unstructured":"K.O'sheaandR.Nash \u201cAn Introduction To Convolutional Neural Networks \u201darXiv preprint arXiv:1511.08458(2015)."},{"issue":"11","key":"e_1_2_9_22_1","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1145\/3422622","article-title":"Generative Adversarial Networks","volume":"63","author":"Goodfellow I.","year":"2020","journal-title":"Communications of The ACM"},{"issue":"7398","key":"e_1_2_9_23_1","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1038\/nature11082","article-title":"Topological Domains In Mammalian Genomes Identified By Analysis Of Chromatin Interactions","volume":"485","author":"Dixon J. R.","year":"2012","journal-title":"Nature"},{"issue":"7398","key":"e_1_2_9_24_1","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1038\/nature11049","article-title":"Spatial Partitioning Of The Regulatory Landscape Of The X\u2010Inactivation Centre","volume":"485","author":"Nora E. P.","year":"2012","journal-title":"Nature"},{"issue":"7527","key":"e_1_2_9_25_1","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1038\/nature13986","article-title":"Topologically Associating Domains Are Stable Units Of Replication\u2010Timing Regulation","volume":"515","author":"Pope B. D.","year":"2014","journal-title":"Nature"},{"issue":"11","key":"e_1_2_9_26_1","doi-asserted-by":"crossref","first-page":"862","DOI":"10.3390\/genes10110862","article-title":"HiCNN2: Enhancing The Resolution Of Hi\u2010C Data Using An Ensemble Of Convolutional Neural Networks","volume":"10","author":"Liu T.","year":"2019","journal-title":"Genes"},{"issue":"5558","key":"e_1_2_9_27_1","doi-asserted-by":"crossref","first-page":"1306","DOI":"10.1126\/science.1067799","article-title":"Capturing Chromosome Conformation","volume":"295","author":"Dekker J.","year":"2002","journal-title":"Science"},{"issue":"21","key":"e_1_2_9_28_1","first-page":"E2191","article-title":"Global View Of Enhancer\u2010Promoter Interactome In Human Cells","volume":"111","author":"He B.","year":"2014","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"},{"key":"e_1_2_9_29_1","doi-asserted-by":"crossref","unstructured":"Z.Tu H.Talebi H.Zhang et\u00a0al. \u201cMaxim: Multi\u2010Axis Map For Image Processing \u201d inProceedings of The IEEE\/CVF Conference on Computer Vision and Pattern Recognition(2022) 5769\u20135780.","DOI":"10.1109\/CVPR52688.2022.00568"},{"issue":"2","key":"e_1_2_9_30_1","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1007287","article-title":"Deephic: A Generative Adversarial Network For Enhancing Hi\u2010C Data Resolution","volume":"16","author":"Hong H.","year":"2020","journal-title":"PLOS Computational Biology"},{"issue":"02","key":"e_1_2_9_31_1","doi-asserted-by":"crossref","DOI":"10.1142\/S0219720021500013","article-title":"Rehic: Enhancing Hi\u2010C Data Resolution Via Residual Convolutional Network","volume":"19","author":"Cheng Z.","year":"2021","journal-title":"Journal of Bioinformatics and Computational Biology"},{"issue":"1","key":"e_1_2_9_32_1","doi-asserted-by":"crossref","first-page":"8880","DOI":"10.1038\/s41598-021-88115-9","article-title":"VEHiCLE: A Variationally Encoded Hi\u2010C Loss Enhancement Algorithm For Improving And Generating Hi\u2010C Data","volume":"11","author":"Highsmith M.","year":"2021","journal-title":"Scientific Reports"},{"issue":"3","key":"e_1_2_9_33_1","doi-asserted-by":"crossref","first-page":"288","DOI":"10.3390\/biology14030288","article-title":"Enhancing Single\u2010Cell And Bulk Hi\u2010C Data Using A Generative Transformer Model","volume":"14","author":"Gao R.","year":"2025","journal-title":"Biology"},{"key":"e_1_2_9_34_1","doi-asserted-by":"crossref","first-page":"353","DOI":"10.3389\/fgene.2020.00353","article-title":"Srhic: A Deep Learning Model To Enhance The Resolution Of Hi\u2010C Data","volume":"11","author":"Li Z.","year":"2020","journal-title":"Frontiers in Genetics"},{"issue":"7","key":"e_1_2_9_35_1","doi-asserted-by":"crossref","first-page":"e70","DOI":"10.1093\/nar\/gkv1505","article-title":"TopDom: An Efficient And Deterministic Method For Identifying Topological Domains In Genomes","volume":"44","author":"Shin H.","year":"2016","journal-title":"Nucleic Acids Research"},{"issue":"7296","key":"e_1_2_9_36_1","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1038\/nature08973","article-title":"A Three\u2010Dimensional Model Of The Yeast Genome","volume":"465","author":"Duan Z.","year":"2010","journal-title":"Nature"},{"issue":"3","key":"e_1_2_9_37_1","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1038\/s41596-019-0273-0","article-title":"Identifying Statistically Significant Chromatin Contacts From Hi\u2010C Data With FitHiC2","volume":"15","author":"Kaul A.","year":"2020","journal-title":"Nature Protocols"},{"issue":"1","key":"e_1_2_9_38_1","doi-asserted-by":"crossref","first-page":"D61","DOI":"10.1093\/nar\/gkl842","article-title":"NCBI Reference Sequences (RefSeq): A Curated Non\u2010Redundant Sequence Database Of Genomes, Transcripts And Proteins","volume":"35","author":"Pruitt K. D.","year":"2007","journal-title":"Nucleic Acids Research"},{"issue":"7493","key":"e_1_2_9_39_1","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1038\/nature12787","article-title":"An Atlas Of Active Enhancers Across Human Cell Types And Tissues","volume":"507","author":"Andersson R.","year":"2014","journal-title":"Nature"},{"issue":"7414","key":"e_1_2_9_40_1","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1038\/nature11247","article-title":"An Integrated Encyclopedia Of DNA Elements In The Human Genome","volume":"489","author":"ENCODE Project Consortium","year":"2012","journal-title":"Nature"},{"key":"e_1_2_9_41_1","doi-asserted-by":"crossref","DOI":"10.1093\/database\/bax028","article-title":"GeneHancer: Genome\u2010Wide Integration Of Enhancers And Target Genes In GeneCards","volume":"2017","author":"Fishilevich S.","year":"2017","journal-title":"Database"},{"issue":"12","key":"e_1_2_9_42_1","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1038\/nmeth.4025","article-title":"Micro\u2010C Xl: Assaying Chromosome Conformation From The Nucleosome To The Entire Genome","volume":"13","author":"Hsieh T.\u2010H. S.","year":"2016","journal-title":"Nature Methods"},{"key":"e_1_2_9_43_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10462-009-9124-7","article-title":"Ensemble\u2010Based Classifiers","volume":"33","author":"Rokach L.","year":"2010","journal-title":"Artificial Intelligence Review"},{"key":"e_1_2_9_44_1","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.inffus.2019.06.016","article-title":"Urban Big Data Fusion Based On Deep Learning: An Overview","volume":"53","author":"Liu J.","year":"2020","journal-title":"Information Fusion"},{"key":"e_1_2_9_45_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.imavis.2021.104117","article-title":"Weighted Boxes Fusion: Ensembling Boxes From Different Object Detection Models","volume":"107","author":"Solovyev R.","year":"2021","journal-title":"Image and Vision Computing"},{"key":"e_1_2_9_46_1","unstructured":"Z.Chen Z.Wu E.Zamfir et\u00a0al. \u201cNTIRE 2024 Challenge On Image Super\u2010Resolution (X4): Methods And Results \u201d inProceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition(2024) 6108\u20136132."},{"key":"e_1_2_9_47_1","doi-asserted-by":"crossref","unstructured":"H.Dong J.Pan L.Xiang et\u00a0al. \u201cMulti\u2010Scale Boosted Dehazing Network With Dense Feature Fusion \u201d inProceedings of The IEEE\/CVF Conference on Computer Vision and Pattern Recognition(2020) 2157\u20132167.","DOI":"10.1109\/CVPR42600.2020.00223"},{"issue":"24","key":"e_1_2_9_48_1","doi-asserted-by":"crossref","DOI":"10.1126\/sciadv.abn9215","article-title":"Eaglec: A Deep\u2010Learning Framework For Detecting A Full Range Of Structural Variations From Bulk And Single\u2010Cell Contact Maps","volume":"8","author":"Wang X.","year":"2022","journal-title":"Science Advances"},{"issue":"6","key":"e_1_2_9_49_1","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1038\/s41592-021-01164-w","article-title":"Genome\u2010Wide Detection Of Enhancer\u2010Hijacking Events From Chromatin Interaction Data In Rearranged Genomes","volume":"18","author":"Wang X.","year":"2021","journal-title":"Nature Methods"},{"key":"e_1_2_9_50_1","doi-asserted-by":"crossref","unstructured":"M.Nguyen S.Tang J. L.McClay J. C.Harrell andM. G.Dozmorov \u201cEpitadformer: A Transformer\u2010Based Model For High\u2010Resolution Tad Boundary Detection Using Epigenomic Signal Embeddings \u201dBiorxiv(2026): 2026\u201301.","DOI":"10.64898\/2026.01.20.700691"},{"issue":"1","key":"e_1_2_9_51_1","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.cels.2015.07.012","article-title":"Juicebox Provides A Visualization System For Hi\u2010C Contact Maps With Unlimited Zoom","volume":"3","author":"Durand N. C.","year":"2016","journal-title":"Cell Systems"},{"issue":"1","key":"e_1_2_9_52_1","doi-asserted-by":"crossref","first-page":"1602","DOI":"10.1038\/s41467-022-29258-9","article-title":"Stripenn Detects Architectural Stripes From Chromatin Conformation Data Using Computer Vision","volume":"13","author":"Yoon S.","year":"2022","journal-title":"Nature Communications"},{"issue":"1","key":"e_1_2_9_53_1","doi-asserted-by":"crossref","first-page":"3265","DOI":"10.1038\/s41467-018-05691-7","article-title":"Decoding Topologically Associating Domains With Ultra\u2010Low Resolution Hi\u2010C Data By Graph Structural Entropy","volume":"9","author":"Li A.","year":"2018","journal-title":"Nature Communications"},{"issue":"1","key":"e_1_2_9_54_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-020-02234-6","article-title":"SuperTAD: Robust Detection Of Hierarchical Topologically Associated Domains With Optimized Structural Information","volume":"22","author":"Zhang Y. W.","year":"2021","journal-title":"Genome Biology"},{"issue":"1","key":"e_1_2_9_55_1","doi-asserted-by":"crossref","first-page":"9354","DOI":"10.1038\/s41598-019-45839-z","article-title":"The ENCODE Blacklist: Identification Of Problematic Regions Of The Genome","volume":"9","author":"Amemiya H. M.","year":"2019","journal-title":"Scientific Reports"},{"key":"e_1_2_9_56_1","unstructured":"A.Dosovitskiy L.Beyer A.Kolesnikov et\u00a0al. \u201cAn Image Is Worth 16x16 Words: Transformers For Image Recognition At Scale \u201d inInternational Conference on Learning Representations(2021)."},{"key":"e_1_2_9_57_1","doi-asserted-by":"crossref","unstructured":"Z.Liu Y.Lin Y.Cao et\u00a0al. \u201cSwin Transformer: Hierarchical Vision Transformer Using Shifted Windows \u201d inProceedings of The IEEE\/CVF International Conference on Computer Vision(2021) 10012\u201310022.","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"e_1_2_9_58_1","unstructured":"J.Cao Y.Li K.Zhang andL. V.Gool \u201cVideo Super\u2010Resolution Transformer \u201darXiv preprint arXiv:2106.06847(2021)."},{"key":"e_1_2_9_59_1","doi-asserted-by":"crossref","unstructured":"H.Chen Y.Wang T.Guo et\u00a0al. \u201cPre\u2010Trained Image Processing Transformer \u201d inProceedings of The IEEE\/CVF Conference on Computer Vision and Pattern Recognition(2021) 12299\u201312310.","DOI":"10.1109\/CVPR46437.2021.01212"},{"key":"e_1_2_9_60_1","doi-asserted-by":"crossref","unstructured":"J.Liang J.Cao G.Sun K.Zhang L. V.Gool andR.Timofte \u201cSwinIR: Image Restoration Using Swin Transformer \u201d inProceedings of The IEEE\/CVF International Conference on Computer Vision(2021) 1833\u20131844.","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"e_1_2_9_61_1","doi-asserted-by":"crossref","unstructured":"Z.Wang X.Cun J.Bao W.Zhou J.Liu andH.Li \u201cUformer: A General U\u2010Shaped Transformer For Image Restoration \u201d inProceedings of The IEEE\/CVF Conference on Computer Vision and Pattern Recognition(2022) 17683\u201317693.","DOI":"10.1109\/CVPR52688.2022.01716"},{"key":"e_1_2_9_62_1","doi-asserted-by":"crossref","unstructured":"J.Hu L.Shen andG.Sun \u201cSqueeze\u2010And\u2010Excitation Networks \u201d inProceedings of the IEEE Conference on Computer Vision and Pattern Recognition(2018) 7132\u20137141.","DOI":"10.1109\/CVPR.2018.00745"},{"key":"e_1_2_9_63_1","doi-asserted-by":"crossref","unstructured":"S.Woo J.Park J.\u2010Y.Lee andI. S.Kweon \u201cCBAM: Convolutional Block Attention Module \u201d inProceedings of the European Conference on Computer Vision (ECCV)(2018) 3\u201319.","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"e_1_2_9_64_1","first-page":"1","article-title":"Root Mean Square Error (RMSE) Or Mean Absolute Error (MAE): When To Use Them Or Not","volume":"2022","author":"Hodson T. O.","year":"2022","journal-title":"Geoscientific Model Development Discussions"},{"key":"e_1_2_9_65_1","unstructured":"D. P.KingmaandJ.Ba \u201cAdam: A Method For Stochastic Optimization \u201darXiv preprint arXiv:1412.6980(2014)."},{"issue":"1","key":"e_1_2_9_66_1","doi-asserted-by":"crossref","first-page":"2365","DOI":"10.1038\/s41467-022-29697-4","article-title":"The 4D Nucleome Data Portal As A Resource For Searching And Visualizing Curated Nucleomics Data","volume":"13","author":"Reiff S. B.","year":"2022","journal-title":"Nature Communications"},{"issue":"1","key":"e_1_2_9_67_1","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.cels.2016.07.002","article-title":"Juicer Provides A One\u2010Click System For Analyzing Loop\u2010Resolution Hi\u2010C Experiments","volume":"3","author":"Durand N. C.","year":"2016","journal-title":"Cell Systems"},{"issue":"3","key":"e_1_2_9_68_1","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1093\/imanum\/drs019","article-title":"A Fast Algorithm For Matrix Balancing","volume":"33","author":"Knight P. A.","year":"2013","journal-title":"IMA Journal of Numerical Analysis"},{"issue":"10","key":"e_1_2_9_69_1","doi-asserted-by":"crossref","first-page":"999","DOI":"10.1038\/nmeth.2148","article-title":"Iterative Correction Of Hi\u2010C Data Reveals Hallmarks Of Chromosome Organization","volume":"9","author":"Imakaev M.","year":"2012","journal-title":"Nature methods"},{"key":"e_1_2_9_70_1","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.ymeth.2014.10.031","article-title":"The Hitchhiker's Guide To Hi\u2010C Analysis: Practical Guidelines","volume":"72","author":"Lajoie B. R.","year":"2015","journal-title":"Methods"},{"issue":"347","key":"e_1_2_9_71_1","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1098\/rspl.1895.0041","article-title":"Note On Regression And Inheritance In The Case Of Two Parents","volume":"58","author":"Pearson K.","year":"1895","journal-title":"Proceedings of the Royal Society of London"},{"issue":"3","key":"e_1_2_9_72_1","doi-asserted-by":"crossref","first-page":"441","DOI":"10.2307\/1422689","article-title":"The Proof And Measurement Of Association Between Two Things","volume":"100","author":"Spearman C.","year":"1987","journal-title":"The American Journal of Psychology"},{"issue":"13","key":"e_1_2_9_73_1","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1049\/el:20080522","article-title":"Scope Of Validity Of PSNR in Image\/Video Quality Assessment","volume":"44","author":"Huynh\u2010Thu Q.","year":"2008","journal-title":"Electronics Letters"},{"issue":"4","key":"e_1_2_9_74_1","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image Quality Assessment: From Error Visibility To Structural Similarity","volume":"13","author":"Wang Z.","year":"2004","journal-title":"IEEE Transactions on Image Processing"},{"issue":"3","key":"e_1_2_9_75_1","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1038\/nmeth.1906","article-title":"ChromHMM: Automating Chromatin\u2010State Discovery And Characterization","volume":"9","author":"Ernst J.","year":"2012","journal-title":"Nature Methods"},{"issue":"10","key":"e_1_2_9_76_1","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1038\/nbt1010-1045","article-title":"The NIH Roadmap Epigenomics Mapping Consortium","volume":"28","author":"Bernstein B. E.","year":"2010","journal-title":"Nature Biotechnology"}],"container-title":["Advanced Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/advs.202524180","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/advs.202524180","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/advs.202524180","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T04:49:22Z","timestamp":1788929362000},"score":1,"resource":{"primary":{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/10.1002\/advs.202524180"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,8]]},"references-count":75,"alternative-id":["10.1002\/advs.202524180"],"URL":"https:\/\/doi.org\/10.1002\/advs.202524180","archive":["Portico"],"relation":{},"ISSN":["2198-3844","2198-3844"],"issn-type":[{"value":"2198-3844","type":"print"},{"value":"2198-3844","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,8]]},"assertion":[{"value":"2025-11-29","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-10","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-09-08","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e24180"}}