{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T17:03:59Z","timestamp":1775581439487,"version":"3.50.1"},"reference-count":75,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2022,12,18]],"date-time":"2022-12-18T00:00:00Z","timestamp":1671321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2412019ZD013"],"award-info":[{"award-number":["2412019ZD013"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2412019FZ051"],"award-info":[{"award-number":["2412019FZ051"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["61976050"],"award-info":[{"award-number":["61976050"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["61972384"],"award-info":[{"award-number":["61972384"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,19]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Exploring the potential long noncoding RNA (lncRNA)-disease associations (LDAs) plays a critical role for understanding disease etiology and pathogenesis. Given the high cost of biological experiments, developing a computational method is a practical necessity to effectively accelerate experimental screening process of candidate LDAs. However, under the high sparsity of LDA dataset, many computational models hardly exploit enough knowledge to learn comprehensive patterns of node representations. Moreover, although the metapath-based GNN has been recently introduced into LDA prediction, it discards intermediate nodes along the meta-path and results in information loss. Results: This paper presents a new multi-view contrastive heterogeneous graph attention network (GAT) for lncRNA-disease association prediction, MCHNLDA for brevity. Specifically, MCHNLDA firstly leverages rich biological data sources of lncRNA, gene and disease to construct two-view graphs, feature structural graph of feature schema view and lncRNA-gene-disease heterogeneous graph of network topology view. Then, we design a cross-contrastive learning task to collaboratively guide graph embeddings of the two views without relying on any labels. In this way, we can pull closer the nodes of similar features and network topology, and push other nodes away. Furthermore, we propose a heterogeneous contextual GAT, where long short-term memory network is incorporated into attention mechanism to effectively capture sequential structure information along the meta-path. Extensive experimental comparisons against several state-of-the-art methods show the effectiveness of proposed framework.The code and data of proposed framework is freely available at\u00a0https:\/\/github.com\/zhaoxs686\/MCHNLDA.<\/jats:p>","DOI":"10.1093\/bib\/bbac548","type":"journal-article","created":{"date-parts":[[2022,12,18]],"date-time":"2022-12-18T12:57:16Z","timestamp":1671368236000},"source":"Crossref","is-referenced-by-count":33,"title":["Multi-view contrastive heterogeneous graph attention network for lncRNA\u2013disease association prediction"],"prefix":"10.1093","volume":"24","author":[{"given":"Xiaosa","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, Northeast Normal University , Changchun 130117, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Northeast Normal University , Changchun 130117, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaowei","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Northeast Normal University , Changchun 130117, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minghao","family":"Yin","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Northeast Normal University , Changchun 130117, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,12,18]]},"reference":[{"issue":"9","key":"2023011917132952400_ref1","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.1101\/gr.132159.111","article-title":"The gencode v7 catalog of human long noncoding rnas: analysis of their gene structure, evolution, and expression","volume":"22","author":"Derrien","year":"2012","journal-title":"Genome Res"},{"issue":"7385","key":"2023011917132952400_ref2","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1038\/nature10887","article-title":"Modular regulatory principles of large non-coding rnas","volume":"482","author":"Guttman","year":"2012","journal-title":"Nature"},{"issue":"6","key":"2023011917132952400_ref3","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1016\/j.molcel.2011.08.018","article-title":"Molecular mechanisms of long noncoding rnas","volume":"43","author":"Wang","year":"2011","journal-title":"Mol Cell"},{"issue":"6","key":"2023011917132952400_ref4","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1016\/j.tcb.2011.04.001","article-title":"Long noncoding rnas and human disease","volume":"21","author":"Wapinski","year":"2011","journal-title":"Trends Cell Biol"},{"issue":"2","key":"2023011917132952400_ref5","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.nbd.2011.12.006","article-title":"Long non-coding rnas in huntington\u2019s disease neurodegeneration","volume":"46","author":"Johnson","year":"2012","journal-title":"Neurobiol Dis"},{"issue":"2","key":"2023011917132952400_ref6","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1016\/j.atherosclerosis.2011.11.017","article-title":"Genetic variants at the 9p21 locus contribute to atherosclerosis through modulation of anril and cdkn2a\/b","volume":"220","author":"Congrains","year":"2012","journal-title":"Atherosclerosis"},{"issue":"7","key":"2023011917132952400_ref7","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1038\/nm1784","article-title":"Expression of a noncoding rna is elevated in alzheimer\u2019s disease and drives rapid feed-forward regulation of $\\beta$-secretase","volume":"14","author":"Faghihi","year":"2008","journal-title":"Nat Med"},{"issue":"3","key":"2023011917132952400_ref8","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.ccr.2007.07.027","article-title":"Ultraconserved regions encoding ncrnas are altered in human leukemias and carcinomas","volume":"12","author":"Calin","year":"2007","journal-title":"Cancer Cell"},{"issue":"11","key":"2023011917132952400_ref9","doi-asserted-by":"crossref","first-page":"5134","DOI":"10.1158\/0008-5472.CAN-07-0465","article-title":"X inactive\u2013specific transcript rna coating and genetic instability of the x chromosome in brca1 breast tumors","volume":"67","author":"Vincent-Salomon","year":"2007","journal-title":"Cancer Res"},{"issue":"3","key":"2023011917132952400_ref10","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1002\/(SICI)1096-9896(199711)183:3<345::AID-PATH930>3.0.CO;2-8","article-title":"Expression of neural bc200 rna in human tumours","volume":"183","author":"Chen","year":"1997","journal-title":"J Pathol"},{"issue":"1","key":"2023011917132952400_ref11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s13721-015-0081-6","article-title":"Inferring disease associations of the long non-coding rnas through non-negative matrix factorization","volume":"4","author":"Biswas","year":"2015","journal-title":"Netw Model Anal Health Inform Bioinforma"},{"issue":"8","key":"2023011917132952400_ref12","doi-asserted-by":"crossref","first-page":"2420","DOI":"10.1109\/JBHI.2019.2958389","article-title":"Predicting human lncrna-disease associations based on geometric matrix completion","volume":"24","author":"Lu","year":"2019","journal-title":"IEEE J Biomed Health"},{"issue":"19","key":"2023011917132952400_ref13","doi-asserted-by":"crossref","first-page":"3357","DOI":"10.1093\/bioinformatics\/bty327","article-title":"Prediction of lncrna\u2013disease associations based on inductive matrix completion","volume":"34","author":"Lu","year":"2018","journal-title":"Bioinformatics"},{"issue":"9","key":"2023011917132952400_ref14","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.1093\/bioinformatics\/btx794","article-title":"Matrix factorization-based data fusion for the prediction of lncrna\u2013disease associations","volume":"34","author":"Fu","year":"2018","journal-title":"Bioinformatics"},{"key":"2023011917132952400_ref15","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.ymeth.2019.06.015","article-title":"Weighted matrix factorization on multi-relational data for lncrna-disease association prediction","volume":"173","author":"Wang","year":"2020","journal-title":"Methods"},{"key":"2023011917132952400_ref16","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.neucom.2020.02.062","article-title":"Ldgrnmf: Lncrna-disease associations prediction based on graph regularized non-negative matrix factorization","volume":"424","author":"Wang","year":"2021","journal-title":"Neurocomputing"},{"issue":"20","key":"2023011917132952400_ref17","doi-asserted-by":"crossref","first-page":"2617","DOI":"10.1093\/bioinformatics\/btt426","article-title":"Novel human lncrna\u2013disease association inference based on lncrna expression profiles","volume":"29","author":"Chen","year":"2013","journal-title":"Bioinformatics"},{"issue":"1","key":"2023011917132952400_ref18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12859-019-2985-0","article-title":"A novel collaborative filtering model for lncrna-disease association prediction based on the na\u00efve bayesian classifier","volume":"20","author":"Yu","year":"2019","journal-title":"BMC bioinformatics"},{"issue":"3","key":"2023011917132952400_ref19","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1093\/bioinformatics\/btw639","article-title":"Ldap: a web server for lncrna-disease association prediction","volume":"33","author":"Lan","year":"2017","journal-title":"Bioinformatics"},{"key":"2023011917132952400_ref20","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1016\/j.isci.2019.08.030","article-title":"A learning-based method for lncrna-disease association identification combing similarity information and rotation forest","volume":"19","author":"Guo","year":"2019","journal-title":"IScience"},{"issue":"1","key":"2023011917132952400_ref21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12859-021-04104-9","article-title":"Ipcarf: improving lncrna-disease association prediction using incremental principal component analysis feature selection and a random forest classifier","volume":"22","author":"Zhu","year":"2021","journal-title":"BMC bioinformatics"},{"issue":"3","key":"2023011917132952400_ref22","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1039\/C4MB00511B","article-title":"Prioritizing candidate disease-related long non-coding rnas by walking on the heterogeneous lncrna and disease network","volume":"11","author":"Zhou","year":"2015","journal-title":"Mol Biosyst"},{"issue":"1","key":"2023011917132952400_ref23","first-page":"1","article-title":"Global prioritizing disease candidate lncrnas via a multi-level composite network","volume":"7","author":"Yao","year":"2017","journal-title":"Sci Rep"},{"issue":"36","key":"2023011917132952400_ref24","doi-asserted-by":"crossref","first-page":"57919","DOI":"10.18632\/oncotarget.11141","article-title":"Irwrlda: improved random walk with restart for lncrna-disease association prediction","volume":"7","author":"Chen","year":"2016","journal-title":"Oncotarget"},{"issue":"1","key":"2023011917132952400_ref25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12859-019-2675-y","article-title":"Prediction of lncrna-disease associations by integrating diverse heterogeneous information sources with rwr algorithm and positive pointwise mutual information","volume":"20","author":"Fan","year":"2019","journal-title":"BMC bioinformatics"},{"key":"2023011917132952400_ref26","article-title":"Lda-lnsubrw: lncrna-disease association prediction based on linear neighborhood similarity and unbalanced bi-random walk","volume":"19","author":"Xie","year":"2020","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2023011917132952400_ref27","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"arXiv","author":"Kipf"},{"key":"2023011917132952400_ref28","article-title":"Graph attention networks","volume-title":"arXiv","author":"Veli\u010dkovi\u0107"},{"key":"2023011917132952400_ref29","volume-title":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","author":"Han"},{"issue":"3","key":"2023011917132952400_ref30","doi-asserted-by":"crossref","first-page":"bbaa146","DOI":"10.1093\/bib\/bbaa146","article-title":"Predicting human microbe\u2013disease associations via graph attention networks with inductive matrix completion","volume":"22","author":"Long","year":"2021","journal-title":"Brief Bioinform"},{"key":"2023011917132952400_ref31","doi-asserted-by":"crossref","first-page":"107282","DOI":"10.1016\/j.compbiolchem.2020.107282","article-title":"Inferring LncRNA-disease associations based on graph autoencoder matrix completion","volume":"87","author":"Wu","year":"2020","journal-title":"Comput Biol Chem"},{"issue":"9","key":"2023011917132952400_ref32","doi-asserted-by":"crossref","first-page":"1012","DOI":"10.3390\/cells8091012","article-title":"Graph convolutional network and convolutional neural network based method for predicting lncrna-disease associations","volume":"8","author":"Xuan","year":"2019","journal-title":"Cell"},{"key":"2023011917132952400_ref33","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbaa391","article-title":"Gaerf: predicting lncrna-disease associations by graph auto-encoder and random forest","volume":"22","author":"Wu","year":"2021","journal-title":"Brief Bioinform"},{"key":"2023011917132952400_ref34","doi-asserted-by":"crossref","first-page":"2264","DOI":"10.1109\/TCBB.2021.3070910","article-title":"Graph convolutional auto-encoders for predicting novel lncrna-disease associations","volume":"19","author":"Silva","year":"2022","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2023011917132952400_ref35","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1016\/j.neucom.2020.09.094","article-title":"Ganlda: graph attention network for lncrna-disease associations prediction","volume":"469","author":"Lan","year":"2022","journal-title":"Neurocomputing"},{"issue":"1","key":"2023011917132952400_ref36","doi-asserted-by":"crossref","first-page":"bbab361","DOI":"10.1093\/bib\/bbab361","article-title":"Gcrflda: scoring lncrna-disease associations using graph convolution matrix completion with conditional random field","volume":"23","author":"Fan","year":"2022","journal-title":"Brief Bioinform"},{"issue":"2","key":"2023011917132952400_ref37","doi-asserted-by":"crossref","first-page":"bbab604","DOI":"10.1093\/bib\/bbab604","article-title":"Multi-channel graph attention autoencoders for disease-related lncrnas prediction","volume":"23","author":"Sheng","year":"2022","journal-title":"Brief Bioinform"},{"key":"2023011917132952400_ref38","first-page":"1","article-title":"Extra trees method for predicting lncrna-disease association based on multi-layer graph embedding aggregation","volume":"2021","author":"Wu","year":"2021","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"issue":"5","key":"2023011917132952400_ref39","doi-asserted-by":"crossref","first-page":"bbac361","DOI":"10.1093\/bib\/bbac361","article-title":"Learning global dependencies and multi-semantics within heterogeneous graph for predicting disease-related lncrnas","volume":"23","author":"Xuan","year":"2022","journal-title":"Brief Bioinform"},{"issue":"1","key":"2023011917132952400_ref40","doi-asserted-by":"crossref","first-page":"bbab407","DOI":"10.1093\/bib\/bbab407","article-title":"Heterogeneous graph attention network based on meta-paths for lncrna\u2013disease association prediction","volume":"23","author":"Zhao","year":"2022","journal-title":"Brief Bioinform"},{"key":"2023011917132952400_ref41","first-page":"19","volume-title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","author":"Zhao"},{"key":"2023011917132952400_ref42","first-page":"2921","volume-title":"Proceedings of the Web Conference","author":"Wang"},{"issue":"8","key":"2023011917132952400_ref43","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput"},{"issue":"D1","key":"2023011917132952400_ref44","doi-asserted-by":"crossref","first-page":"D1034","DOI":"10.1093\/nar\/gky905","article-title":"Lncrnadisease 2.0: an updated database of long non-coding rna-associated diseases","volume":"47","author":"Bao","year":"2019","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"2023011917132952400_ref45","doi-asserted-by":"crossref","first-page":"D1251","DOI":"10.1093\/nar\/gkaa1006","article-title":"Lnc2cancer 3.0: an updated resource for experimentally supported lncrna\/circrna cancer associations and web tools based on rna-seq and scrna-seq data","volume":"49","author":"Gao","year":"2021","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"2023011917132952400_ref46","doi-asserted-by":"crossref","first-page":"D326","DOI":"10.1093\/nar\/gkab997","article-title":"Rnainter v4. 0: Rna interactome repository with redefined confidence scoring system and improved accessibility","volume":"50","author":"Kang","year":"2022","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"2023011917132952400_ref47","doi-asserted-by":"crossref","first-page":"D833","DOI":"10.1093\/nar\/gkw943","article-title":"Disgenet: a comprehensive platform integrating information on human disease-associated genes and variants","volume":"45","author":"Pi\u00f1ero","year":"2017","journal-title":"Nucleic Acids Res"},{"issue":"4","key":"2023011917132952400_ref48","doi-asserted-by":"crossref","first-page":"1805","DOI":"10.1109\/JBHI.2018.2870728","article-title":"Hergepred: heterogeneous network embedding representation for disease gene prediction","volume":"23","author":"Kuo Yang","year":"2018","journal-title":"IEEE J Biomed health"},{"issue":"1","key":"2023011917132952400_ref49","first-page":"1","article-title":"Constructing lncrna functional similarity network based on lncrna-disease associations and disease semantic similarity","volume":"5","author":"Chen","year":"2015","journal-title":"Sci Rep"},{"issue":"13","key":"2023011917132952400_ref50","doi-asserted-by":"crossref","first-page":"1644","DOI":"10.1093\/bioinformatics\/btq241","article-title":"Inferring the human microrna functional similarity and functional network based on microrna-associated diseases","volume":"26","author":"Wang","year":"2010","journal-title":"Bioinformatics"},{"issue":"D1","key":"2023011917132952400_ref51","doi-asserted-by":"crossref","first-page":"D573","DOI":"10.1093\/nar\/gky1126","article-title":"Humannet v2: human gene networks for disease research","volume":"47","author":"Hwang","year":"2019","journal-title":"Nucleic Acids Res"},{"issue":"4","key":"2023011917132952400_ref52","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1109\/TCBB.2016.2550432","article-title":"Inferring microrna-disease associations by random walk on a heterogeneous network with multiple data sources","volume":"14","author":"Liu","year":"2016","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"issue":"21","key":"2023011917132952400_ref53","doi-asserted-by":"crossref","first-page":"3036","DOI":"10.1093\/bioinformatics\/btr500","article-title":"Gaussian interaction profile kernels for predicting drug\u2013target interaction","volume":"27","author":"Van Laarhoven","year":"2011","journal-title":"Bioinformatics"},{"key":"2023011917132952400_ref54","first-page":"2022","volume-title":"The World Wide Web Conference","author":"Wang"},{"key":"2023011917132952400_ref55","first-page":"1726","volume-title":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","author":"Wang"},{"issue":"8","key":"2023011917132952400_ref56","doi-asserted-by":"crossref","first-page":"2538","DOI":"10.1093\/bioinformatics\/btz965","article-title":"Neural inductive matrix completion with graph convolutional networks for mirna-disease association prediction","volume":"36","author":"Li","year":"2020","journal-title":"Bioinformatics"},{"issue":"27","key":"2023011917132952400_ref57","first-page":"88","article-title":"Cost-sensitive learning with neural networks","volume":"15","author":"Kukar","year":"1998","journal-title":"ECAI"},{"key":"2023011917132952400_ref58","article-title":"A brief review of deep multi-task learning and auxiliary task learning","volume-title":"arXiv","author":"Vafaeikia"},{"key":"2023011917132952400_ref59","article-title":"Adam: A method for stochastic optimization","volume-title":"arXiv","author":"Kingma"},{"key":"2023011917132952400_ref60","article-title":"Deep graph library: A graph-centric, highly-performant package for graph neural networks","volume-title":"arXiv","author":"Wang"},{"key":"2023011917132952400_ref61","doi-asserted-by":"crossref","first-page":"5401","DOI":"10.1109\/TCOMM.2022.3184160","article-title":"Secure and energy-efficient uav relay communications exploiting collaborative beamforming","volume":"70","author":"Sun","year":"2022","journal-title":"IEEE Trans Commun"},{"issue":"2","key":"2023011917132952400_ref62","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1109\/TCYB.2017.2780274","article-title":"Improving metaheuristic algorithms with information feedback models","volume":"49","author":"Wang","year":"2017","journal-title":"IEEE Trans Cybern"},{"key":"2023011917132952400_ref63a","doi-asserted-by":"crossref","DOI":"10.1016\/j.artint.2019.103230","article-title":"Sccwalk: An efficient local search algorithm and its improvements for maximum weight clique problem","volume":"280","author":"Wang","year":"2020","journal-title":"Artif Intell"},{"key":"2023011917132952400_ref64a","article-title":"Improved local search for the minimum weight dominating set problem in massive graphs by using a deep optimization mechanism","volume":"314","author":"Chen","year":"2022","journal-title":"Artif Intell"},{"key":"2023011917132952400_ref63","first-page":"329","volume-title":"Conference of the Canadian Society for Computational Studies of Intelligence","author":"Ling"},{"issue":"3","key":"2023011917132952400_ref64","doi-asserted-by":"crossref","first-page":"e0118432","DOI":"10.1371\/journal.pone.0118432","article-title":"The precision-recall plot is more informative than the roc plot when evaluating binary classifiers on imbalanced datasets","volume":"10","author":"Saito","year":"2015","journal-title":"PLoS One"},{"key":"2023011917132952400_ref67a","article-title":"Identifying drug\u2013target interactions via heterogeneous graph attention networks combined with cross-modal similarities","volume":"23","author":"","journal-title":"Brief Bioinform"},{"issue":"4","key":"2023011917132952400_ref65","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1002\/bimj.200410135","article-title":"Estimation of the youden index and its associated cutoff point","volume":"47","author":"Fluss","year":"2005","journal-title":"Biom J"},{"key":"2023011917132952400_ref66","first-page":"871","volume-title":"2020 IEEE International Conference on Data Mining (ICDM)","author":"Zhao"},{"key":"2023011917132952400_ref67","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.biomaterials.2017.11.019","article-title":"Development of a theranostic prodrug for colon cancer therapy by combining ligand-targeted delivery and enzyme-stimulated activation","volume":"155","author":"Sharma","year":"2018","journal-title":"Biomaterials"},{"issue":"1","key":"2023011917132952400_ref68","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12943-017-0583-1","article-title":"The lncrna crnde promotes colorectal cancer cell proliferation and chemoresistance via mir-181a-5p-mediated regulation of wnt\/$\\beta$-catenin signaling","volume":"16","author":"Han","year":"2017","journal-title":"Mol Cancer"},{"issue":"1","key":"2023011917132952400_ref69","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1186\/s13046-018-0771-x","article-title":"Lncrna tug1 promoted kiaa1199 expression via mir-600 to accelerate cell metastasis and epithelial-mesenchymal transition in colorectal cancer","volume":"37","author":"Sun","year":"2018","journal-title":"J Exp Clin Cancer Res"},{"issue":"1","key":"2023011917132952400_ref70","doi-asserted-by":"crossref","first-page":"9","DOI":"10.3322\/caac.21208","article-title":"Cancer statistics, 2014","volume":"64","author":"Siegel","year":"2014","journal-title":"CA Cancer J Clin"},{"issue":"3","key":"2023011917132952400_ref71","doi-asserted-by":"crossref","first-page":"1313","DOI":"10.1159\/000495550","article-title":"Lncrna malat1 promotes cancer metastasis in osteosarcoma via activation of the pi3k-akt signaling pathway","volume":"51","author":"Chen","year":"2018","journal-title":"Cell Physiol Biochem"},{"issue":"6","key":"2023011917132952400_ref72","doi-asserted-by":"crossref","first-page":"1092","DOI":"10.3349\/ymj.2017.58.6.1092","article-title":"Knockdown of long non-coding rna neat1 inhibits proliferation and invasion and induces apoptosis of osteosarcoma by inhibiting mir-194 expression","volume":"58","author":"Heping Wang","year":"2017","journal-title":"Yonsei Med J"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/24\/1\/bbac548\/48783220\/bbac548.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/24\/1\/bbac548\/48783220\/bbac548.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,12]],"date-time":"2023-03-12T01:12:33Z","timestamp":1678583553000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbac548\/6931723"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,18]]},"references-count":75,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1,19]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbac548","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2023,1]]},"published":{"date-parts":[[2022,12,18]]},"article-number":"bbac548"}}