{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T00:47:17Z","timestamp":1743036437506,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":32,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819947485"},{"type":"electronic","value":"9789819947492"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-981-99-4749-2_42","type":"book-chapter","created":{"date-parts":[[2023,7,29]],"date-time":"2023-07-29T23:02:17Z","timestamp":1690671737000},"page":"497-508","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prediction of circRNA-Binding Protein Site Based on Hybrid Neural Networks and Recurrent Forests Method"],"prefix":"10.1007","author":[{"given":"Zewen","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingfang","family":"Meng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,30]]},"reference":[{"key":"42_CR1","doi-asserted-by":"crossref","unstructured":"Rong, D., et al.: An emerging function of circrna-mirnas-mrna axis in human diseases. Oncotarget 8(42), 73271 (2017)","DOI":"10.18632\/oncotarget.19154"},{"issue":"11","key":"42_CR2","doi-asserted-by":"publisher","first-page":"3852","DOI":"10.1073\/pnas.73.11.3852","volume":"73","author":"HL Sanger","year":"1976","unstructured":"Sanger, H.L., Klotz, G., Riesner, D., Gross, H.J., Kleinschmidt, A.K.: Viroids are single-stranded covalently closed circular rna molecules existing as highly basepaired rod-like structures. Proc. Natl. Acad. Sci. 73(11), 3852\u20133856 (1976)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"42_CR3","doi-asserted-by":"publisher","first-page":"53","DOI":"10.3389\/fgene.2016.00053","volume":"7","author":"D Lu","year":"2016","unstructured":"Lu, D., Xu, A.D.: Mini review: circular rnas as potential clinical biomarkers for disorders in the central nervous system. Front. Genet. 7, 53 (2016)","journal-title":"Front. Genet."},{"issue":"6","key":"42_CR4","doi-asserted-by":"publisher","first-page":"1071","DOI":"10.1007\/s00018-017-2688-5","volume":"75","author":"LM Holdt","year":"2018","unstructured":"Holdt, L.M., Kohlmaier, A., Teupser, D.: Molecular roles and function of circular RNAS in eukaryotic cells. Cell. Mol. Life Sci. 75(6), 1071\u20131098 (2018)","journal-title":"Cell. Mol. Life Sci."},{"issue":"7441","key":"42_CR5","doi-asserted-by":"publisher","first-page":"384","DOI":"10.1038\/nature11993","volume":"495","author":"TB Hansen","year":"2013","unstructured":"Hansen, T.B., et al.: Natural RNA circles function as efficient microrna sponges. Nature 495(7441), 384\u2013388 (2013)","journal-title":"Nature"},{"issue":"2","key":"42_CR6","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/j.canlet.2015.06.003","volume":"365","author":"S Qu","year":"2015","unstructured":"Qu, S., et al.: Circular RNA: a new star of noncoding rnas. Cancer Lett. 365(2), 141\u2013148 (2015)","journal-title":"Cancer Lett."},{"key":"42_CR7","doi-asserted-by":"crossref","unstructured":"Ebbesen, K.K., Kjems, J., Hansen, T.B.: Circular rnas: identification, biogenesis and function. Biochimica et Biophysica Acta (BBA)-Gene Regulatory Mechanisms 1859(1), 163\u2013168 (2016)","DOI":"10.1016\/j.bbagrm.2015.07.007"},{"key":"42_CR8","doi-asserted-by":"crossref","unstructured":"Zhang, B., Chen, M., Jiang, N., Shi, K., Qian, R.: A regulatory circuit of circmto1\/mir-17\/qki-5 inhibits the proliferation of lung adenocarcinoma. Cancer Biol. Therapy 20(8), 1127\u20131135 (2019). (Prediction of circRNA-binding protein site 15)","DOI":"10.1080\/15384047.2019.1598762"},{"key":"42_CR9","doi-asserted-by":"crossref","unstructured":"Wang, R., et al.: Eif4a3-induced circular rna mmp9 (circmmp9) acts as a sponge of mir-124 and promotes glioblastoma multiforme cell tumorigenesis. Mol. Cancer 17(1), 1\u201312 (2018)","DOI":"10.1186\/s12943-018-0911-0"},{"key":"42_CR10","doi-asserted-by":"crossref","unstructured":"He, Z., et al.: Fus\/circ_002136\/mir-138-5p\/sox13 feedback loop regulates angiogenesis in glioma. J. Exp. Clin. Cancer Res. 38, 1\u201319 (2019)","DOI":"10.1186\/s13046-019-1065-7"},{"issue":"2","key":"42_CR11","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1002\/wrna.1103","volume":"3","author":"M Ascano","year":"2012","unstructured":"Ascano, M., Hafner, M., Cekan, P., Gerstberger, S., Tuschl, T.: Identification of rna\u2013protein interaction networks using par-clip. Wiley Interdiscipl. Rev. RNA 3(2), 159\u2013177 (2012)","journal-title":"Wiley Interdiscipl. Rev. RNA"},{"key":"42_CR12","doi-asserted-by":"crossref","unstructured":"Barnes, C., Kanhere, A.: Identification of rna\u2013protein interactions through in vitro RNA pull-down assays. Polycomb Group Proteins: Methods and Protocols, pp. 99\u2013113 (2016)","DOI":"10.1007\/978-1-4939-6380-5_9"},{"key":"42_CR13","doi-asserted-by":"crossref","unstructured":"Ju, Y., Yuan, L., Yang, Y., Zhao, H.: Circslnn: identifying rbp-binding sites on circrnas via sequence labeling neural networks. Front. Genetics 1184 (2019)","DOI":"10.3389\/fgene.2019.01184"},{"issue":"12","key":"42_CR14","doi-asserted-by":"publisher","first-page":"1604","DOI":"10.1261\/rna.070565.119","volume":"25","author":"K Zhang","year":"2019","unstructured":"Zhang, K., Pan, X., Yang, Y., Shen, H.B.: Crip: predicting circrna\u2013rbp-binding sites using a codon-based encoding and hybrid deep neural networks. RNA 25(12), 1604\u20131615 (2019)","journal-title":"RNA"},{"issue":"22","key":"42_CR15","doi-asserted-by":"publisher","first-page":"4035","DOI":"10.3390\/molecules24224035","volume":"24","author":"Z Wang","year":"2019","unstructured":"Wang, Z., Lei, X., Wu, F.X.: Identifying cancer-specific circrna\u2013rbp binding sites based on deep learning. Molecules 24(22), 4035 (2019)","journal-title":"Molecules"},{"issue":"15","key":"42_CR16","doi-asserted-by":"publisher","first-page":"4276","DOI":"10.1093\/bioinformatics\/btaa522","volume":"36","author":"C Jia","year":"2020","unstructured":"Jia, C., Bi, Y., Chen, J., Leier, A., Li, F., Song, J.: Passion: an ensemble neural network approach for identifying the binding sites of rbps on circrnas. Bioinformatics 36(15), 4276\u20134282 (2020)","journal-title":"Bioinformatics"},{"key":"42_CR17","doi-asserted-by":"crossref","unstructured":"Yang, Y., Hou, Z., Ma, Z., Li, X., Wong, K.C.: icircrbp-dhn: identification of circrna-rbp interaction sites using deep hierarchical network. Briefings Bioinform. 22(4), bbaa274 (2021)","DOI":"10.1093\/bib\/bbaa274"},{"issue":"1","key":"42_CR18","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1009798","volume":"18","author":"M Niu","year":"2022","unstructured":"Niu, M., Zou, Q., Lin, C.: Crbpdl: identification of circrna-rbp interaction sites using an ensemble neural network approach. PLoS Comput. Biol. 18(1), e1009798 (2022)","journal-title":"PLoS Comput. Biol."},{"key":"42_CR19","doi-asserted-by":"crossref","unstructured":"Li, H., et al.: circrna-binding protein site prediction based on multi-view deep learning, subspace learning and multi-view classifier. Briefings Bioinform. 23(1), bbab394 (2022)","DOI":"10.1093\/bib\/bbab394"},{"issue":"23","key":"42_CR20","doi-asserted-by":"publisher","first-page":"3150","DOI":"10.1093\/bioinformatics\/bts565","volume":"28","author":"L Fu","year":"2012","unstructured":"Fu, L., Niu, B., Zhu, Z., Wu, S., Li, W.: Cd-hit: accelerated for clustering the next-generation sequencing data. Bioinformatics 28(23), 3150\u20133152 (2012)","journal-title":"Bioinformatics"},{"issue":"6","key":"42_CR21","doi-asserted-by":"publisher","DOI":"10.1002\/wrna.1544","volume":"10","author":"X Pan","year":"2019","unstructured":"Pan, X., Yang, Y., Xia, C.Q., Mirza, A.H., Shen, H.B.: Recent methodology progress of deep learning for RNA\u2013protein interaction prediction. Wiley Interdiscipl. Rev. RNA 10(6), e1544 (2019)","journal-title":"Wiley Interdiscipl. Rev. RNA"},{"key":"42_CR22","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1007\/s12539-015-0124-9","volume":"8","author":"P Feng","year":"2016","unstructured":"Feng, P., Chen, W., Lin, H.: Identifying antioxidant proteins by using optimal dipeptide compositions. Interdiscipl. Sci. Comput. Life Sci. 8, 186\u2013191 (2016)","journal-title":"Interdiscipl. Sci. Comput. Life Sci."},{"issue":"1","key":"42_CR23","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1002\/0471250953.bi1202s26","volume":"26","author":"IL Hofacker","year":"2009","unstructured":"Hofacker, I.L.: R na secondary structure analysis using the vienna rna package. Curr. Protoc. Bioinform. 26(1), 12\u201322 (2009)","journal-title":"Curr. Protoc. Bioinform."},{"issue":"17","key":"42_CR24","doi-asserted-by":"publisher","first-page":"3035","DOI":"10.1093\/bioinformatics\/bty222","volume":"34","author":"S Budach","year":"2018","unstructured":"Budach, S., Marsico, A.: Pysster: classification of biological sequences by learning sequence and structure motifs with convolutional neural networks. Bioinformatics 34(17), 3035\u20133037 (2018)","journal-title":"Bioinformatics"},{"key":"42_CR25","unstructured":"Le, Q., Mikolov, T.: Distributed representations of sentences and documents. In: International Conference on Machine Learning, pp. 1188\u20131196. PMLR (2014)"},{"issue":"11","key":"42_CR26","doi-asserted-by":"publisher","first-page":"1666","DOI":"10.1261\/rna.043687.113","volume":"20","author":"P Gla\u017ear","year":"2014","unstructured":"Gla\u017ear, P., Papavasileiou, P., Rajewsky, N.: Circbase: a database for circular RNAS. RNA 20(11), 1666\u20131670 (2014)","journal-title":"RNA"},{"key":"42_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-021-00444-8","volume":"8","author":"L Alzubaidi","year":"2021","unstructured":"Alzubaidi, L., et al.: Review of deep learning: concepts, cnn architectures, challenges, applications, future directions. J. big Data 8, 1\u201374 (2021)","journal-title":"J. big Data"},{"key":"42_CR28","doi-asserted-by":"crossref","unstructured":"Siami-Namini, S., Tavakoli, N., Namin, A.S.: The performance of lstm and bilstm in forecasting time series. In: 2019 IEEE International Conference on Big Data (Big Data), pp. 3285\u20133292. IEEE (2019)","DOI":"10.1109\/BigData47090.2019.9005997"},{"key":"42_CR29","unstructured":"Benton, A., Khayrallah, H., Gujral, B., Reisinger, D.A., Zhang, S., Arora, R.: Deep generalized canonical correlation analysis. arXiv preprint arXiv:1702.02519 (2017)"},{"issue":"11","key":"42_CR30","doi-asserted-by":"publisher","first-page":"2673","DOI":"10.1109\/78.650093","volume":"45","author":"M Schuster","year":"1997","unstructured":"Schuster, M., Paliwal, K.K.: Bidirectional recurrent neural networks. IEEE Trans. Signal Process. 45(11), 2673\u20132681 (1997)","journal-title":"IEEE Trans. Signal Process."},{"key":"42_CR31","doi-asserted-by":"crossref","unstructured":"Zhou, Z.H., Feng, J.: Deep forest: Towards an alternative to deep neural networks. In: IJCAI, pp. 3553\u20133559 (2017)","DOI":"10.24963\/ijcai.2017\/497"},{"key":"42_CR32","doi-asserted-by":"publisher","first-page":"2452","DOI":"10.1109\/TSP.2021.3061218","volume":"69","author":"M S\u00f8rensen","year":"2021","unstructured":"S\u00f8rensen, M., Kanatsoulis, C.I., Sidiropoulos, N.D.: Generalized canonical correlation analysis: a subspace intersection approach. IEEE Trans. Signal Process. 69, 2452\u20132467 (2021)","journal-title":"IEEE Trans. Signal Process."}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-4749-2_42","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T06:06:50Z","timestamp":1693548410000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-4749-2_42"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819947485","9789819947492"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-4749-2_42","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"30 July 2023","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":"Zhengzhou","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 August 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2023a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2023\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}