{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T07:29:23Z","timestamp":1781940563152,"version":"3.54.5"},"publisher-location":"Cham","reference-count":57,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030608019","type":"print"},{"value":"9783030608026","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-60802-6_44","type":"book-chapter","created":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T18:04:35Z","timestamp":1602612275000},"page":"505-513","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Novel Computational Method for Predicting LncRNA-Disease Associations from Heterogeneous Information Network with SDNE Embedding Model"],"prefix":"10.1007","author":[{"given":"Ping","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo-Wei","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leon","family":"Wong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhu-Hong","family":"You","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen-Hao","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hai-Cheng","family":"Yi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,10,5]]},"reference":[{"issue":"6","key":"44_CR1","doi-asserted-by":"publisher","first-page":"1225","DOI":"10.1007\/s00438-014-0882-9","volume":"289","author":"J Lv","year":"2014","unstructured":"Lv, J., et al.: Identification and characterization of long intergenic non-coding RNAs related to mouse liver development. Mol. Genet. Genom. 289(6), 1225\u20131235 (2014). https:\/\/doi.org\/10.1007\/s00438-014-0882-9","journal-title":"Mol. Genet. Genom."},{"key":"44_CR2","doi-asserted-by":"publisher","first-page":"815","DOI":"10.1016\/j.cell.2007.02.029","volume":"128","author":"C Yanofsky","year":"2007","unstructured":"Yanofsky, C.: Establishing the triplet nature of the genetic code. Cell 128, 815\u2013818 (2007)","journal-title":"Cell"},{"key":"44_CR3","doi-asserted-by":"publisher","first-page":"1845","DOI":"10.1126\/science.1162228","volume":"322","author":"LJ Core","year":"2008","unstructured":"Core, L.J., Waterfall, J.J., Lis, J.T.: Nascent RNA sequencing reveals widespread pausing and divergent initiation at human promoters. Science 322, 1845\u20131848 (2008)","journal-title":"Science"},{"key":"44_CR4","first-page":"558","volume":"18","author":"X Chen","year":"2016","unstructured":"Chen, X., Yan, C.C., Zhang, X., You, Z.: Long non-coding RNAs and complex diseases: from experimental results to computational models. Brief. Bioinform. 18, 558\u2013576 (2016)","journal-title":"Brief. Bioinform."},{"key":"44_CR5","doi-asserted-by":"crossref","unstructured":"Chen, X., et al.: NRDTD: a database for clinically or experimentally supported non-coding RNAs and drug targets associations. Database 2017 (2017)","DOI":"10.1093\/database\/bax057"},{"key":"44_CR6","doi-asserted-by":"publisher","first-page":"25902","DOI":"10.18632\/oncotarget.8296","volume":"7","author":"Y Huang","year":"2016","unstructured":"Huang, Y., Chen, X., You, Z., Huang, D., Chan, K.C.C.: ILNCSIM: improved lncRNA functional similarity calculation model. Oncotarget 7, 25902\u201325914 (2016)","journal-title":"Oncotarget"},{"key":"44_CR7","doi-asserted-by":"crossref","unstructured":"Guo, Z., You, Z., Wang, Y., Yi, H., Chen, Z.: A learning-based method for LncRNA-disease association identification combing similarity information and rotation forest. iScience 19, 786\u2013795 (2019)","DOI":"10.1016\/j.isci.2019.08.030"},{"key":"44_CR8","doi-asserted-by":"publisher","first-page":"57919","DOI":"10.18632\/oncotarget.11141","volume":"7","author":"X Chen","year":"2016","unstructured":"Chen, X., You, Z.-H., Yan, G.-Y., Gong, D.-W.: IRWRLDA: improved random walk with restart for lncRNA-disease association prediction. Oncotarget 7, 57919 (2016)","journal-title":"Oncotarget"},{"key":"44_CR9","doi-asserted-by":"publisher","first-page":"345","DOI":"10.3390\/genes9070345","volume":"9","author":"J Yu","year":"2018","unstructured":"Yu, J., Ping, P., Wang, L., Kuang, L., Li, X., Wu, Z.: A novel probability model for lncRNA\u2013disease association prediction based on the na\u00efve bayesian classifier. Genes 9, 345 (2018)","journal-title":"Genes"},{"key":"44_CR10","doi-asserted-by":"publisher","first-page":"476","DOI":"10.3389\/fgene.2019.00476","volume":"10","author":"L Ou-Yang","year":"2019","unstructured":"Ou-Yang, L., et al.: LncRNA-disease association prediction using two-side sparse self-representation. Front. Genet. 10, 476 (2019)","journal-title":"Front. Genet."},{"key":"44_CR11","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1186\/1471-2105-11-343","volume":"11","author":"Z You","year":"2010","unstructured":"You, Z., Yin, Z., Han, K., Huang, D., Zhou, X.: A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network. BMC Bioinf. 11, 343 (2010)","journal-title":"BMC Bioinf."},{"key":"44_CR12","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1109\/TAC.2016.2578645","volume":"62","author":"S Li","year":"2017","unstructured":"Li, S., Zhou, M., Luo, X., You, Z.: Distributed winner-take-all in dynamic networks. IEEE Trans. Autom. Control 62, 577\u2013589 (2017)","journal-title":"IEEE Trans. Autom. Control"},{"key":"44_CR13","doi-asserted-by":"publisher","first-page":"3178","DOI":"10.1093\/bioinformatics\/bty333","volume":"34","author":"X Chen","year":"2018","unstructured":"Chen, X., Xie, D., Wang, L., Zhao, Q., You, Z., Liu, H.: BNPMDA: bipartite network projection for MiRNA\u2013disease association prediction. Bioinformatics 34, 3178\u20133186 (2018)","journal-title":"Bioinformatics"},{"key":"44_CR14","doi-asserted-by":"crossref","unstructured":"Wang, M., You, Z., Wang, L., Li, L., Zheng, K.: LDGRNMF: LncRNA-disease associations prediction based on graph regularized non-negative matrix factorization. Neurocomputing (2020)","DOI":"10.1016\/j.neucom.2020.02.062"},{"key":"44_CR15","doi-asserted-by":"crossref","unstructured":"Ma, L., et al.: Multi-neighborhood learning for global alignment in biological networks. IEEE\/ACM Trans. Comput. Biol. Bioinf. (2020)","DOI":"10.1109\/TCBB.2020.2985838"},{"key":"44_CR16","doi-asserted-by":"publisher","first-page":"e21502","DOI":"10.1371\/journal.pone.0021502","volume":"6","author":"P Yang","year":"2011","unstructured":"Yang, P., Li, X., Wu, M., Kwoh, C.-K., Ng, S.-K.: Inferring gene-phenotype associations via global protein complex network propagation. PloS One 6, e21502 (2011)","journal-title":"PloS One"},{"key":"44_CR17","doi-asserted-by":"publisher","first-page":"2074","DOI":"10.1039\/C3MB70608G","volume":"10","author":"J Sun","year":"2014","unstructured":"Sun, J., et al.: Inferring novel lncRNA\u2013disease associations based on a random walk model of a lncRNA functional similarity network. Mol. BioSyst. 10, 2074\u20132081 (2014)","journal-title":"Mol. BioSyst."},{"key":"44_CR18","doi-asserted-by":"publisher","first-page":"760","DOI":"10.1039\/C4MB00511B","volume":"11","author":"M Zhou","year":"2015","unstructured":"Zhou, M., et al.: Prioritizing candidate disease-related long non-coding RNAs by walking on the heterogeneous lncRNA and disease network. Mol. BioSyst. 11, 760\u2013769 (2015)","journal-title":"Mol. BioSyst."},{"key":"44_CR19","doi-asserted-by":"publisher","first-page":"1065","DOI":"10.1038\/s41598-018-19357-3","volume":"8","author":"L Ding","year":"2018","unstructured":"Ding, L., Wang, M., Sun, D., Li, A.: TPGLDA: novel prediction of associations between lncRNAs and diseases via lncRNA-disease-gene tripartite graph. Sci. Rep. 8, 1065 (2018)","journal-title":"Sci. Rep."},{"key":"44_CR20","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1186\/s12918-018-0527-4","volume":"12","author":"T Mori","year":"2018","unstructured":"Mori, T., Ngouv, H., Hayashida, M., Akutsu, T., Nacher, J.C.: ncRNA-disease association prediction based on sequence information and tripartite network. BMC Syst. Biol. 12, 37 (2018)","journal-title":"BMC Syst. Biol."},{"key":"44_CR21","doi-asserted-by":"publisher","first-page":"688","DOI":"10.1109\/TCBB.2018.2827373","volume":"16","author":"P Ping","year":"2018","unstructured":"Ping, P., Wang, L., Kuang, L., Ye, S., Iqbal, M.F.B., Pei, T.: A novel method for lncRNA-disease association prediction based on an lncRNA-disease association network. IEEE\/ACM Trans. Comput. Biol. Bioinf. 16, 688\u2013693 (2018)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf."},{"key":"44_CR22","doi-asserted-by":"publisher","first-page":"888","DOI":"10.3389\/fphys.2019.00888","volume":"10","author":"M Sumathipala","year":"2019","unstructured":"Sumathipala, M., Maiorino, E., Weiss, S.T., Sharma, A.: Network diffusion approach to predict lncRNA disease associations using multi-type biological networks: LION. Front. Physiol. 10, 888 (2019)","journal-title":"Front. Physiol."},{"key":"44_CR23","doi-asserted-by":"publisher","first-page":"1106","DOI":"10.3389\/fgene.2019.01106","volume":"10","author":"H Yi","year":"2019","unstructured":"Yi, H., You, Z., Guo, Z.: Construction and analysis of molecular association network by combining behavior representation and node attributes. Front. Genet. 10, 1106 (2019)","journal-title":"Front. Genet."},{"key":"44_CR24","doi-asserted-by":"publisher","first-page":"866","DOI":"10.3390\/cells8080866","volume":"8","author":"Z-H Guo","year":"2019","unstructured":"Guo, Z.-H., Yi, H.-C., You, Z.-H.: Construction and comprehensive analysis of a molecular associations network via lncRNA-miRNA-disease-drug-protein graph. Cells 8, 866 (2019)","journal-title":"Cells"},{"key":"44_CR25","unstructured":"Yi, H.-C., You, Z.-H., Huang, W.-Z., Guo, Z.-H., Wang, Y.-B., Cheng, Z.-H.: Construction of large-scale heterogeneous molecular association network and its application in molecular link prediction. In: Basic & Clinical Pharmacology & Toxicology, p. 5. Wiley, Hoboken (2019)"},{"key":"44_CR26","doi-asserted-by":"crossref","unstructured":"Yi, H.C., You, Z.H., Guo, Z.H., Huang, D.S., Kcc, C.: learning representation of molecules in association network for predicting intermolecular associations. IEEE\/ACM Trans. Comput. Biol. Bioinf. 1 (2020)","DOI":"10.1109\/TCBB.2020.2973091"},{"key":"44_CR27","doi-asserted-by":"publisher","first-page":"498","DOI":"10.1016\/j.omtn.2019.10.046","volume":"19","author":"Z Guo","year":"2020","unstructured":"Guo, Z., You, Z., Yi, H.: Integrative construction and analysis of molecular association network in human cells by fusing node attribute and behavior information. Mol. Ther. Nucleic Acids 19, 498\u2013506 (2020)","journal-title":"Mol. Ther. Nucleic Acids"},{"key":"44_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s42003-019-0734-6","volume":"3","author":"Z-H Guo","year":"2020","unstructured":"Guo, Z.-H., You, Z.-H., Huang, D.-S., Yi, H.-C., Chen, Z.-H., Wang, Y.-B.: A learning based framework for diverse biomolecule relationship prediction in molecular association network. Commun. Biol. 3, 1\u20139 (2020)","journal-title":"Commun. Biol."},{"key":"44_CR29","doi-asserted-by":"crossref","unstructured":"Guo, Z., You, Z., Yi, H., Zheng, K., Wang, Y.: MeSHHeading2vec: a new method for representing MeSH headings as feature vectors based on graph embedding algorithm. bioRxiv 835637 (2019)","DOI":"10.1101\/835637"},{"key":"44_CR30","doi-asserted-by":"publisher","first-page":"giaa032","DOI":"10.1093\/gigascience\/giaa032","volume":"9","author":"Z-H Guo","year":"2020","unstructured":"Guo, Z.-H., You, Z.-H., Wang, Y.-B., Huang, D.-S., Yi, H.-C., Chen, Z.-H.: Bioentity2vec: attribute-and behavior-driven representation for predicting multi-type relationships between bioentities. GigaScience 9, giaa032 (2020)","journal-title":"GigaScience"},{"key":"44_CR31","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1093\/bib\/bbx130","volume":"20","author":"X Chen","year":"2019","unstructured":"Chen, X., Xie, D., Zhao, Q., You, Z.: MicroRNAs and complex diseases: from experimental results to computational models. Brief. Bioinform. 20, 515\u2013539 (2019)","journal-title":"Brief. Bioinform."},{"key":"44_CR32","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1093\/bioinformatics\/btw715","volume":"33","author":"X Chen","year":"2016","unstructured":"Chen, X., Huang, Y., You, Z., Yan, G., Wang, X.: A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases. Bioinformatics 33, 733\u2013739 (2016)","journal-title":"Bioinformatics"},{"key":"44_CR33","doi-asserted-by":"publisher","first-page":"e1005455","DOI":"10.1371\/journal.pcbi.1005455","volume":"13","author":"Z You","year":"2017","unstructured":"You, Z., et al.: PBMDA: a novel and effective path-based computational model for miRNA-disease association prediction. PLOS Comput. Biol. 13, e1005455 (2017)","journal-title":"PLOS Comput. Biol."},{"key":"44_CR34","doi-asserted-by":"publisher","first-page":"e1007872","DOI":"10.1371\/journal.pcbi.1007872","volume":"16","author":"K Zheng","year":"2020","unstructured":"Zheng, K., You, Z.-H., Li, J.-Q., Wang, L., Guo, Z.-H., Huang, Y.-A.: iCDA-CGR: Identification of circRNA-disease associations based on chaos game representation. PLoS Comput. Biol. 16, e1007872 (2020)","journal-title":"PLoS Comput. Biol."},{"key":"44_CR35","doi-asserted-by":"crossref","unstructured":"Wang, L., You, Z., Li, Y., Zheng, K., Huang, Y.: GCNCDA: a new method for predicting CircRNA-disease associations based on graph convolutional network algorithm. bioRxiv 858837 (2019)","DOI":"10.1101\/858837"},{"key":"44_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-019-56847-4","volume":"10","author":"B-Y Ji","year":"2020","unstructured":"Ji, B.-Y., You, Z.-H., Cheng, L., Zhou, J.-R., Alghazzawi, D., Li, L.-P.: Predicting miRNA-disease association from heterogeneous information network with GraRep embedding model. Sci. Rep. 10, 1\u201312 (2020)","journal-title":"Sci. Rep."},{"key":"44_CR37","doi-asserted-by":"publisher","first-page":"602","DOI":"10.1016\/j.omtn.2019.12.010","volume":"19","author":"K Zheng","year":"2020","unstructured":"Zheng, K., You, Z.-H., Wang, L., Zhou, Y., Li, L.-P., Li, Z.-W.: Dbmda: A unified embedding for sequence-based mirna similarity measure with applications to predict and validate mirna-disease associations. Mol. Ther.-Nucleic Acids 19, 602\u2013611 (2020)","journal-title":"Mol. Ther.-Nucleic Acids"},{"key":"44_CR38","doi-asserted-by":"publisher","first-page":"133314","DOI":"10.1109\/ACCESS.2019.2940470","volume":"7","author":"K Zheng","year":"2019","unstructured":"Zheng, K., Wang, L., You, Z.: CGMDA: an approach to predict and validate MicroRNA-disease associations by utilizing chaos game representation and LightGBM. IEEE Access 7, 133314\u2013133323 (2019)","journal-title":"IEEE Access"},{"key":"44_CR39","doi-asserted-by":"publisher","first-page":"37578","DOI":"10.1109\/ACCESS.2020.2974349","volume":"8","author":"M Wang","year":"2020","unstructured":"Wang, M., You, Z., Li, L., Wong, L., Chen, Z., Gan, C.: GNMFLMI: graph regularized nonnegative matrix factorization for predicting LncRNA-MiRNA interactions. IEEE Access 8, 37578\u201337588 (2020)","journal-title":"IEEE Access"},{"key":"44_CR40","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1111\/jcmm.14583","volume":"24","author":"L Wong","year":"2020","unstructured":"Wong, L., Huang, Y.A., You, Z.H., Chen, Z.H., Cao, M.Y.: LNRLMI: linear neighbour representation for predicting lncRNA-miRNA interactions. J. Cell Mol. Med. 24, 79\u201387 (2020)","journal-title":"J. Cell Mol. Med."},{"key":"44_CR41","doi-asserted-by":"crossref","unstructured":"Hu, P., Huang, Y., Chan, K.C.C., You, Z.: Learning multimodal networks from heterogeneous data for prediction of lncRNA-miRNA interactions. IEEE\/ACM Trans. Comput. Biol. Bioinf. 1 (2019)","DOI":"10.1109\/TCBB.2019.2957094"},{"key":"44_CR42","doi-asserted-by":"publisher","first-page":"758","DOI":"10.3389\/fgene.2019.00758","volume":"10","author":"Y Huang","year":"2019","unstructured":"Huang, Y., et al.: Predicting lncRNA-miRNA Interaction via graph convolution auto-encoder. Front. Genet. 10, 758 (2019)","journal-title":"Front. Genet."},{"key":"44_CR43","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1186\/s12920-018-0429-8","volume":"11","author":"Z Huang","year":"2018","unstructured":"Huang, Z., Huang, Y., You, Z., Zhu, Z., Sun, Y.: Novel link prediction for large-scale miRNA-lncRNA interaction network in a bipartite graph. BMC Med. Genom. 11, 113 (2018)","journal-title":"BMC Med. Genom."},{"key":"44_CR44","doi-asserted-by":"publisher","first-page":"D276","DOI":"10.1093\/nar\/gkx1004","volume":"46","author":"Y-R Miao","year":"2017","unstructured":"Miao, Y.-R., Liu, W., Zhang, Q., Guo, A.-Y.: lncRNASNP2: an updated database of functional SNPs and mutations in human and mouse lncRNAs. Nucleic Acids Res. 46, D276\u2013D280 (2017)","journal-title":"Nucleic Acids Res."},{"key":"44_CR45","doi-asserted-by":"publisher","first-page":"D983","DOI":"10.1093\/nar\/gks1099","volume":"41","author":"G Chen","year":"2012","unstructured":"Chen, G., et al.: LncRNADisease: a database for long-non-coding RNA-associated diseases. Nucleic Acids Res. 41, D983\u2013D986 (2012)","journal-title":"Nucleic Acids Res."},{"key":"44_CR46","doi-asserted-by":"publisher","first-page":"D140","DOI":"10.1093\/nar\/gky1051","volume":"47","author":"L Cheng","year":"2018","unstructured":"Cheng, L., et al.: LncRNA2Target v2.0: a comprehensive database for target genes of lncRNAs in human and mouse. Nucleic Acids Res. 47, D140\u2013D144 (2018)","journal-title":"Nucleic Acids Res."},{"key":"44_CR47","doi-asserted-by":"publisher","first-page":"D1013","DOI":"10.1093\/nar\/gky1010","volume":"47","author":"Z Huang","year":"2018","unstructured":"Huang, Z., et al.: HMDD v3.0: a database for experimentally supported human microRNA\u2013disease associations. Nucleic acids research 47, D1013\u2013D1017 (2018)","journal-title":"Nucleic acids research"},{"key":"44_CR48","doi-asserted-by":"crossref","unstructured":"Pi\u00f1ero, J., et al.: DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res. gkw943 (2016)","DOI":"10.1093\/nar\/gkw943"},{"key":"44_CR49","doi-asserted-by":"publisher","first-page":"e58201","DOI":"10.1371\/journal.pone.0058201","volume":"8","author":"AP Davis","year":"2013","unstructured":"Davis, A.P., et al.: Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the comparative toxicogenomics database. PLoS One 8, e58201 (2013)","journal-title":"PLoS One"},{"key":"44_CR50","doi-asserted-by":"publisher","first-page":"D296","DOI":"10.1093\/nar\/gkx1067","volume":"46","author":"C-H Chou","year":"2017","unstructured":"Chou, C.-H., et al.: miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res. 46, D296\u2013D302 (2017)","journal-title":"Nucleic Acids Res."},{"key":"44_CR51","doi-asserted-by":"publisher","first-page":"D1074","DOI":"10.1093\/nar\/gkx1037","volume":"46","author":"DS Wishart","year":"2017","unstructured":"Wishart, D.S., et al.: DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 46, D1074\u2013D1082 (2017)","journal-title":"Nucleic Acids Res."},{"key":"44_CR52","doi-asserted-by":"crossref","unstructured":"Szklarczyk, D., et al.: The STRING database in 2017: quality-controlled protein\u2013protein association networks, made broadly accessible. Nucleic Acids Res. gkw937 (2016)","DOI":"10.1093\/nar\/gkw937"},{"key":"44_CR53","doi-asserted-by":"publisher","first-page":"D155","DOI":"10.1093\/nar\/gky1141","volume":"47","author":"A Kozomara","year":"2018","unstructured":"Kozomara, A., Birgaoanu, M., Griffiths-Jones, S.: miRBase: from microRNA sequences to function. Nucleic Acids Res. 47, D155\u2013D162 (2018)","journal-title":"Nucleic Acids Res."},{"key":"44_CR54","doi-asserted-by":"publisher","first-page":"D308","DOI":"10.1093\/nar\/gkx1107","volume":"46","author":"S Fang","year":"2017","unstructured":"Fang, S., et al.: NONCODEV5: a comprehensive annotation database for long non-coding RNAs. Nucleic Acids Res. 46, D308\u2013D314 (2017)","journal-title":"Nucleic Acids Res."},{"key":"44_CR55","doi-asserted-by":"publisher","first-page":"4337","DOI":"10.1073\/pnas.0607879104","volume":"104","author":"J Shen","year":"2007","unstructured":"Shen, J., et al.: Predicting protein\u2013protein interactions based only on sequences information. Proc. Natl. Acad. Sci. 104, 4337\u20134341 (2007)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"44_CR56","doi-asserted-by":"crossref","unstructured":"Wang, D., Cui, P., Zhu, W.: Structural deep network embedding. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1225\u20131234. ACM (2016)","DOI":"10.1145\/2939672.2939753"},{"key":"44_CR57","doi-asserted-by":"crossref","unstructured":"Chen, T., Guestrin, C.: XGboost: a scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785\u2013794 (2016)","DOI":"10.1145\/2939672.2939785"}],"container-title":["Lecture Notes in Computer Science","Intelligent Computing Theories and Application"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-60802-6_44","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T17:37:25Z","timestamp":1696873045000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-60802-6_44"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030608019","9783030608026"],"references-count":57,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-60802-6_44","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"5 October 2020","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":"Bari","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ic-ic.tongji.edu.cn\/2020\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}