{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T03:29:42Z","timestamp":1767065382955,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":22,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819756919"},{"type":"electronic","value":"9789819756926"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-5692-6_6","type":"book-chapter","created":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T08:02:35Z","timestamp":1722326555000},"page":"62-71","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Cluster Analysis of Scrna-Seq Data Combining Bioinformatics with Graph Attention Autoencoders and Ensemble Clustering"],"prefix":"10.1007","author":[{"given":"Lin","family":"Yuan","sequence":"first","affiliation":[]},{"given":"Zhijie","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Zhujun","family":"Li","sequence":"additional","affiliation":[]},{"given":"Shoukang","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Chunyu","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Wendong","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Hongwei","family":"Wei","sequence":"additional","affiliation":[]},{"given":"Xingang","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yushui","family":"Geng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,31]]},"reference":[{"key":"6_CR1","doi-asserted-by":"publisher","first-page":"618","DOI":"10.1038\/nrg3542","volume":"14","author":"E Shapiro","year":"2013","unstructured":"Shapiro, E., Biezuner, T., Linnarsson, S.: Single-cell sequencing-based technologies will revolutionize whole-organism science. Nat. Rev. Genet. 14, 618\u2013630 (2013)","journal-title":"Nat. Rev. Genet."},{"key":"6_CR2","doi-asserted-by":"publisher","first-page":"610","DOI":"10.1016\/j.molcel.2015.04.005","volume":"58","author":"AA Kolodziejczyk","year":"2015","unstructured":"Kolodziejczyk, A.A., Kim, J.K., Svensson, V., et al.: The Technology and Biology of Single-Cell RNA Sequencing. Mol. Cell 58, 610\u2013620 (2015)","journal-title":"Mol. Cell"},{"key":"6_CR3","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1011344","volume":"19","author":"L Yuan","year":"2023","unstructured":"Yuan, L., Zhao, J., Shen, Z., et al.: ICircDA-NEAE: Accelerated attribute network embedding and dynamic convolutional autoencoder for circRNA-disease associations prediction. PLoS Comput. Biol. 19, e1011344 (2023)","journal-title":"PLoS Comput. Biol."},{"key":"6_CR4","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1186\/s12859-021-04256-8","volume":"22","author":"L Yuan","year":"2021","unstructured":"Yuan, L., Zhao, J., Sun, T., et al.: A machine learning framework that integrates multi-omics data predicts cancer-related LncRNAs. BMC Bioinform. 22, 332 (2021)","journal-title":"BMC Bioinform."},{"key":"6_CR5","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1109\/TCBB.2018.2866836","volume":"16","author":"L Yuan","year":"2018","unstructured":"Yuan, L., Guo, L.-H., Yuan, C.-A., et al.: Integration of multi-omics data for gene regulatory network inference and application to breast cancer. IEEE\/ACM Trans. Computat. Biol. Bioinform. 16, 782\u2013791 (2018)","journal-title":"IEEE\/ACM Trans. Computat. Biol. Bioinform."},{"key":"6_CR6","doi-asserted-by":"publisher","first-page":"1154","DOI":"10.1109\/TCBB.2016.2609420","volume":"14","author":"L Yuan","year":"2016","unstructured":"Yuan, L., Zhu, L., Guo, W.-L., et al.: Nonconvex penalty based low-rank representation and sparse regression for eQTL mapping. IEEE\/ACM Trans. Comput. Biol. Bioinform. 14, 1154\u20131164 (2016)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"6_CR7","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1186\/s12864-022-08820-1","volume":"23","author":"Z Shen","year":"2022","unstructured":"Shen, Z., Shao, Y.L., Liu, W., et al.: Prediction of Back-splicing sites for CircRNA formation based on convolutional neural networks. BMC Genomics 23, 581 (2022)","journal-title":"BMC Genomics"},{"key":"6_CR8","doi-asserted-by":"publisher","first-page":"2338","DOI":"10.1038\/s41467-020-15851-3","volume":"11","author":"X Li","year":"2020","unstructured":"Li, X., Wang, K., Lyu, Y., et al.: Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis. Nat. Commun. 11, 2338 (2020)","journal-title":"Nat. Commun."},{"key":"6_CR9","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1038\/s41467-018-07931-2","volume":"10","author":"G Eraslan","year":"2019","unstructured":"Eraslan, G., Simon, L.M., Mircea, M., et al.: Single-cell RNA-seq denoising using a deep count autoencoder. Nat. Commun. 10, 390 (2019)","journal-title":"Nat. Commun."},{"key":"6_CR10","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1038\/s42256-019-0037-0","volume":"1","author":"T Tian","year":"2019","unstructured":"Tian, T., Wan, J., Song, Q., et al.: Clustering single-cell RNA-seq data with a model-based deep learning approach. Nat. Mach. Intell. 1, 191\u2013198 (2019)","journal-title":"Nat. Mach. Intell."},{"key":"6_CR11","doi-asserted-by":"crossref","unstructured":"Chen, L., Wang, W., Zhai, Y., et al.: Deep soft K-means clustering with self-training for single-cell RNA sequence data. NAR Genomics and Bioinform. 2 (2020)","DOI":"10.1093\/nargab\/lqaa039"},{"key":"6_CR12","doi-asserted-by":"publisher","first-page":"2128","DOI":"10.1038\/s41467-017-02001-5","volume":"8","author":"K Bach","year":"2017","unstructured":"Bach, K., Pensa, S., Grzelak, M., et al.: Differentiation dynamics of mammary epithelial cells revealed by single-cell RNA sequencing. Nat. Commun. 8, 2128 (2017)","journal-title":"Nat. Commun."},{"key":"6_CR13","doi-asserted-by":"publisher","first-page":"3227","DOI":"10.1016\/j.celrep.2017.03.004","volume":"18","author":"R Chen","year":"2017","unstructured":"Chen, R., Wu, X., Jiang, L., et al.: Single-Cell RNA-Seq Reveals Hypothalamic Cell Diversity. Cell Rep. 18, 3227\u20133241 (2017)","journal-title":"Cell Rep."},{"key":"6_CR14","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1016\/j.cels.2016.09.002","volume":"3","author":"MJ Muraro","year":"2016","unstructured":"Muraro, M.J., Dharmadhikari, G., Gr\u00fcn, D., et al.: A Single-Cell Transcriptome Atlas of the Human Pancreas. Cell Syst. 3, 385-394.e383 (2016)","journal-title":"Cell Syst."},{"key":"6_CR15","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1038\/nn.4462","volume":"20","author":"RA Romanov","year":"2017","unstructured":"Romanov, R.A., Zeisel, A., Bakker, J., et al.: Molecular interrogation of hypothalamic organization reveals distinct dopamine neuronal subtypes. Nat. Neurosci. 20, 176\u2013188 (2017)","journal-title":"Nat. Neurosci."},{"key":"6_CR16","doi-asserted-by":"crossref","unstructured":"Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nat. 562, 367\u2013372 (2018)","DOI":"10.1038\/s41586-018-0590-4"},{"key":"6_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13059-017-1382-0","volume":"19","author":"FA Wolf","year":"2018","unstructured":"Wolf, F.A., Angerer, P., Theis, F.J.: SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 19, 1\u20135 (2018)","journal-title":"Genome Biol."},{"key":"6_CR18","doi-asserted-by":"publisher","first-page":"3108","DOI":"10.1038\/s41467-018-05469-x","volume":"9","author":"B Wang","year":"2018","unstructured":"Wang, B., Pourshafeie, A., Zitnik, M., et al.: Network enhancement as a general method to denoise weighted biological networks. Nat. Commun. 9, 3108 (2018)","journal-title":"Nat. Commun."},{"key":"6_CR19","doi-asserted-by":"publisher","first-page":"2187","DOI":"10.1093\/bioinformatics\/btac099","volume":"38","author":"Y Cheng","year":"2022","unstructured":"Cheng, Y., Ma, X.: ScGAC: a graph attentional architecture for clustering single-cell RNA-seq data. Bioinform. 38, 2187\u20132193 (2022)","journal-title":"Bioinform."},{"key":"6_CR20","first-page":"100","volume":"28","author":"JAH Wong","year":"1979","unstructured":"Wong, J.A.H.: Algorithm AS 136: A K-Means Clustering Algorithm. J. R. Stat. Soc. 28, 100\u2013108 (1979)","journal-title":"J. R. Stat. Soc."},{"key":"6_CR21","doi-asserted-by":"crossref","unstructured":"Wang, Y., Yu, Z., Li, S., et al.: scBGEDA: deep single-cell clustering analysis via a dual denoising autoencoder with bipartite graph ensemble clustering. Bioinform. 39 (2023)","DOI":"10.1093\/bioinformatics\/btad075"},{"key":"6_CR22","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1038\/nbt.3192","volume":"33","author":"R Satija","year":"2015","unstructured":"Satija, R., Farrell, J.A., Gennert, D., et al.: Spatial reconstruction of single-cell gene expression data. Nat. Biotech. 33, 495\u2013502 (2015)","journal-title":"Nat. Biotech."}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5692-6_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T08:09:36Z","timestamp":1722326976000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5692-6_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819756919","9789819756926"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5692-6_6","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"31 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 August 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2024\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}