{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T23:27:03Z","timestamp":1771025223917,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["5R01DA063316, 5R01HG012572"],"award-info":[{"award-number":["5R01DA063316, 5R01HG012572"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,10]]},"DOI":"10.1145\/3746252.3761240","type":"proceedings-article","created":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T23:55:33Z","timestamp":1762559733000},"page":"625-634","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["MUSE: A Multi-slice Joint Analysis Method for Spatial Transcriptomics Experiments"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4696-0042","authenticated-orcid":false,"given":"Ziheng","family":"Duan","sequence":"first","affiliation":[{"name":"University of California, Irvine, Irvine, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9006-4943","authenticated-orcid":false,"given":"Xi","family":"Li","sequence":"additional","affiliation":[{"name":"University of California, Irvine, Irvine, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-4889-644X","authenticated-orcid":false,"given":"Zhiqing","family":"Xiao","sequence":"additional","affiliation":[{"name":"Yale University, New Haven, CT, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5856-5229","authenticated-orcid":false,"given":"Rex","family":"Ying","sequence":"additional","affiliation":[{"name":"Yale University, New Haven, CT, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5970-0509","authenticated-orcid":false,"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of California, Irvine, Irvine, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2025,11,10]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Science Advances","volume":"10","author":"Dai Rujia","year":"2024","unstructured":"Rujia Dai, Tianyao Chu, Ming Zhang, Xuan Wang, Alexandre Jourdon, Feinan Wu, Jessica Mariani, Flora M Vaccarino, Donghoon Lee, John F Fullard, et al., 2024a. Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data. Science Advances, Vol. 10, 21 (2024), eadh2588."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/MedAI62885.2024.00034"},{"key":"e_1_3_2_1_3_1","volume-title":"Science","volume":"384","author":"Deng Chengyu","year":"2024","unstructured":"Chengyu Deng, Sean Whalen, Marilyn Steyert, Ryan Ziffra, Pawel F Przytycki, Fumitaka Inoue, Daniela A Pereira, Davide Capauto, Scott Norton, Flora M Vaccarino, et al., 2024. Massively parallel characterization of regulatory elements in the developing human cortex. Science, Vol. 384, 6698 (2024), eadh0559."},{"key":"e_1_3_2_1_4_1","volume-title":"Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder. Nature communications","author":"Dong Kangning","year":"2022","unstructured":"Kangning Dong and Shihua Zhang. 2022. Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder. Nature communications, Vol. 13, 1 (2022), 1739."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1011444"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1561\/116.00000239"},{"key":"e_1_3_2_1_7_1","volume-title":"Martin Renqiang Min, and Jing Zhang","author":"Duan Ziheng","year":"2024","unstructured":"Ziheng Duan, Dylan Riffle, Ren Li, Junhao Liu, Martin Renqiang Min, and Jing Zhang. 2024a. Impeller: a path-based heterogeneous graph learning method for spatial transcriptomic data imputation. Bioinformatics, Vol. 40, 6 (2024)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3627673.3679574"},{"key":"e_1_3_2_1_9_1","volume-title":"Ahyeon Hwang, Che Yu Lee, Feng Yue, Mark Gerstein, Yu Luan, Matthew Girgenti, and Jing Zhang.","author":"Duan Ziheng","year":"2024","unstructured":"Ziheng Duan, Siwei Xu, Shushrruth Sai Srinivasan, Ahyeon Hwang, Che Yu Lee, Feng Yue, Mark Gerstein, Yu Luan, Matthew Girgenti, and Jing Zhang. 2024c. scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding. Briefings in Bioinformatics, Vol. 25, 2 (2024), bbae096."},{"key":"e_1_3_2_1_10_1","volume-title":"Siwei Xu, Cagatay Dursun, et al.","author":"Emani Prashant S","year":"2024","unstructured":"Prashant S Emani, Jason J Liu, Declan Clarke, Matthew Jensen, Jonathan Warrell, Chirag Gupta, Ran Meng, Che Yu Lee, Siwei Xu, Cagatay Dursun, et al., 2024. Single-cell genomics and regulatory networks for 388 human brains. Science, Vol. 384, 6698 (2024), eadi5199."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1101\/gr.279584.124"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-023-03078-6"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cels.2024.12.001"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41576-023-00586-w"},{"key":"e_1_3_2_1_15_1","volume-title":"Boyi Guo, Melissa Grant-Peters, Heena R Divecha, Madhavi Tippani, Chaichontat Sriworarat, et al.","author":"Huuki-Myers Louise A","year":"2024","unstructured":"Louise A Huuki-Myers, Abby Spangler, Nicholas J Eagles, Kelsey D Montgomery, Sang Ho Kwon, Boyi Guo, Melissa Grant-Peters, Heena R Divecha, Madhavi Tippani, Chaichontat Sriworarat, et al., 2024. A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex. Science, Vol. 384, 6698 (2024), eadh1938."},{"key":"e_1_3_2_1_16_1","volume-title":"Lin Lin, Rosemarie Terwilliger, Alexa-Nicole Sliby, Jiawei Wang, Tuan Nguyen, et al.","author":"Hwang Ahyeon","year":"2025","unstructured":"Ahyeon Hwang, Mario Skarica, Siwei Xu, Jensine Coudriet, Che Yu Lee, Lin Lin, Rosemarie Terwilliger, Alexa-Nicole Sliby, Jiawei Wang, Tuan Nguyen, et al., 2025. Single-cell transcriptomic and chromatin dynamics of the human brain in PTSD. Nature (2025), 1-11."},{"key":"e_1_3_2_1_17_1","volume-title":"Advances in Neural Information Processing Systems","volume":"7","author":"Kambhatla Nanda","year":"1994","unstructured":"Nanda Kambhatla and Todd Leen. 1994. Classifying with gaussian mixtures and clusters. Advances in Neural Information Processing Systems, Vol. 7 (1994)."},{"key":"e_1_3_2_1_18_1","unstructured":"Dominik Klein Giovanni Palla Marius Lange Michal Klein Zoe Piran Manuel Gander Laetitia Meng-Papaxanthos Michael Sterr Lama Saber Changying Jing et al. 2025. Mapping cells through time and space with moscot. Nature (2025) 1-11."},{"key":"e_1_3_2_1_19_1","volume-title":"sensitive and accurate integration of single-cell data with Harmony. Nature methods","author":"Korsunsky Ilya","year":"2019","unstructured":"Ilya Korsunsky, Nghia Millard, Jean Fan, Kamil Slowikowski, Fan Zhang, Kevin Wei, Yuriy Baglaenko, Michael Brenner, Po-ru Loh, and Soumya Raychaudhuri. 2019. Fast, sensitive and accurate integration of single-cell data with Harmony. Nature methods, Vol. 16, 12 (2019), 1289-1296."},{"key":"e_1_3_2_1_20_1","volume-title":"Imputation of spatially-resolved transcriptomes by graph-regularized tensor completion. PLoS computational biology","author":"Li Zhuliu","year":"2021","unstructured":"Zhuliu Li, Tianci Song, Jeongsik Yong, and Rui Kuang. 2021. Imputation of spatially-resolved transcriptomes by graph-regularized tensor completion. PLoS computational biology, Vol. 17, 4 (2021), e1008218."},{"key":"e_1_3_2_1_21_1","first-page":"1124","article-title":"Partial alignment of multislice spatially resolved transcriptomics data","volume":"33","author":"Liu Xinhao","year":"2023","unstructured":"Xinhao Liu, Ron Zeira, and Benjamin J Raphael. 2023. Partial alignment of multislice spatially resolved transcriptomics data. Genome Research, Vol. 33, 7 (2023), 1124-1132.","journal-title":"Genome Research"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-36796-3"},{"key":"e_1_3_2_1_23_1","volume-title":"Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics. Nature Methods","author":"Ma Ying","year":"2024","unstructured":"Ying Ma and Xiang Zhou. 2024. Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics. Nature Methods (2024), 1-14."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"crossref","unstructured":"Kristen R Maynard Leonardo Collado-Torres Lukas M Weber Cedric Uytingco Brianna K Barry Stephen R Williams Joseph L Catallini Matthew N Tran Zachary Besich Madhavi Tippani et al. 2021. Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex. Nature neuroscience Vol. 24 3 (2021) 425-436.","DOI":"10.1038\/s41593-020-00787-0"},{"key":"e_1_3_2_1_25_1","volume-title":"stVCR: Reconstructing spatio-temporal dynamics of cell development using optimal transport. bioRxiv","author":"Peng Qiangwei","year":"2024","unstructured":"Qiangwei Peng, Peijie Zhou, and Tiejun Li. 2024. stVCR: Reconstructing spatio-temporal dynamics of cell development using optimal transport. bioRxiv (2024), 2024-06."},{"key":"e_1_3_2_1_26_1","volume-title":"Science Advances","volume":"10","author":"Pratt Henry E","year":"2024","unstructured":"Henry E Pratt, Gregory Andrews, Nicole Shedd, Nishigandha Phalke, Tongxin Li, Anusri Pampari, Matthew Jensen, Cindy Wen, PsychENCODE Consortium, Michael J Gandal, et al., 2024. Using a comprehensive atlas and predictive models to reveal the complexity and evolution of brain-active regulatory elements. Science Advances, Vol. 10, 21 (2024), eadj4452."},{"key":"e_1_3_2_1_27_1","volume-title":"Identifying multicellular spatiotemporal organization of cells with SpaceFlow. Nature communications","author":"Ren Honglei","year":"2022","unstructured":"Honglei Ren, Benjamin L Walker, Zixuan Cang, and Qing Nie. 2022. Identifying multicellular spatiotemporal organization of cells with SpaceFlow. Nature communications, Vol. 13, 1 (2022), 4076."},{"key":"e_1_3_2_1_28_1","volume-title":"Makayla Hourihan, Shan Jiang, Hao-Chih Lee, Jaroslav Bendl, et al.","author":"Ruzicka W Brad","year":"2024","unstructured":"W Brad Ruzicka, Shahin Mohammadi, John F Fullard, Jose Davila-Velderrain, Sivan Subburaju, Daniel Reed Tso, Makayla Hourihan, Shan Jiang, Hao-Chih Lee, Jaroslav Bendl, et al., 2024. Single-cell multi-cohort dissection of the schizophrenia transcriptome. Science, Vol. 384, 6698 (2024), eadg5136."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.32614\/RJ-2016-021"},{"key":"e_1_3_2_1_30_1","volume-title":"International Conference on Machine Learning. PMLR, 6275-6284","author":"Titouan Vayer","year":"2019","unstructured":"Vayer Titouan, Nicolas Courty, Romain Tavenard, and R\u00e9mi Flamary. 2019. Optimal transport for structured data with application on graphs. In International Conference on Machine Learning. PMLR, 6275-6284."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.05.061"},{"key":"e_1_3_2_1_32_1","volume-title":"scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses. Nature communications","author":"Wang Juexin","year":"2021","unstructured":"Juexin Wang, Anjun Ma, Yuzhou Chang, Jianting Gong, Yuexu Jiang, Ren Qi, Cankun Wang, Hongjun Fu, Qin Ma, and Dong Xu. 2021. scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses. Nature communications, Vol. 12, 1 (2021), 1882."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbae329"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.330110061"},{"key":"e_1_3_2_1_35_1","volume-title":"Science","volume":"384","author":"Wen Cindy","year":"2024","unstructured":"Cindy Wen, Michael Margolis, Rujia Dai, Pan Zhang, Pawel F Przytycki, Daniel D Vo, Arjun Bhattacharya, Nana Matoba, Miao Tang, Chuan Jiao, et al., 2024. Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain. Science, Vol. 384, 6698 (2024), eadh0829."},{"key":"e_1_3_2_1_36_1","volume-title":"SCANPY: large-scale single-cell gene expression data analysis. Genome biology","author":"Wolf F Alexander","year":"2018","unstructured":"F Alexander Wolf, Philipp Angerer, and Fabian J Theis. 2018. SCANPY: large-scale single-cell gene expression data analysis. Genome biology, Vol. 19 (2018), 1-5."},{"key":"e_1_3_2_1_37_1","unstructured":"Yan Xia Cuihua Xia Yi Jiang Yu Chen Jiaqi Zhou Rujia Dai Cong Han Zhongzheng Mao PsychENCODE Consortium Chunyu Liu et al. 2024. Transcriptomic sex differences in postmortem brain samples from patients with psychiatric disorders. Science translational medicine Vol. 16 749 (2024) eadh9974."},{"key":"e_1_3_2_1_38_1","volume-title":"Proceedings of Conference on Neural Information Processing Systems.","author":"Xiao Zhiqing","year":"2024","unstructured":"Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, and Junbo Zhao. 2024. SPA: A Graph Spectral Alignment Perspective for Domain Adaptation. In Proceedings of Conference on Neural Information Processing Systems."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-024-02215-8"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-022-01459-6"}],"event":{"name":"CIKM '25: The 34th ACM International Conference on Information and Knowledge Management","location":"Seoul Republic of Korea","acronym":"CIKM '25","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the 34th ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3746252.3761240","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:01:15Z","timestamp":1765497675000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746252.3761240"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,10]]},"references-count":40,"alternative-id":["10.1145\/3746252.3761240","10.1145\/3746252"],"URL":"https:\/\/doi.org\/10.1145\/3746252.3761240","relation":{},"subject":[],"published":{"date-parts":[[2025,11,10]]},"assertion":[{"value":"2025-11-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}