{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T05:40:10Z","timestamp":1746769210100,"version":"3.40.5"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031876622","type":"print"},{"value":"9783031876639","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-87663-9_13","type":"book-chapter","created":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T05:14:11Z","timestamp":1746767651000},"page":"146-160","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Developing Ensemble Models for\u00a0Predicting the\u00a0Antigenic Evolution"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9636-9800","authenticated-orcid":false,"given":"Artyom","family":"Firstkov","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9443-3610","authenticated-orcid":false,"given":"Majid","family":"Forghani","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,10]]},"reference":[{"issue":"7","key":"13_CR1","first-page":"3291","volume":"14","author":"TA Adjuik","year":"2022","unstructured":"Adjuik, T.A., Ananey-Obiri, D.: Word2vec neural model-based technique to generate protein vectors for combating covid-19: a machine learning approach. Int. J. Inf. Technol. 14(7), 3291\u20133299 (2022)","journal-title":"Int. J. Inf. Technol."},{"key":"13_CR2","unstructured":"Devlin, J.: Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"13_CR3","doi-asserted-by":"publisher","unstructured":"Forghani, M., Firstkov, A., Alyannezhadi, M., Danilenko, D., Komissarov, A.: Reduced amino acid alphabet-based encoding and its impact on modeling influenza antigenic evolution. Russ. J. Infect. Immunity 12(5), 837\u2013849 (2022). https:\/\/doi.org\/10.15789\/2220-7619-RAA-1968","DOI":"10.15789\/2220-7619-RAA-1968"},{"issue":"9","key":"13_CR4","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.3390\/v12091019","volume":"12","author":"M Forghani","year":"2020","unstructured":"Forghani, M., Khachay, M.: Convolutional neural network based approach to in silico non-anticipating prediction of antigenic distance for influenza virus. Viruses 12(9), 1019 (2020)","journal-title":"Viruses"},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Forghani, M., Khachay, M., AlyanNezhadi, M.M.: The impact of amino acid encoding on the prediction of antigenic variants. In: 2020 6th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), pp.\u00a01\u20135. IEEE (2020)","DOI":"10.1109\/ICSPIS51611.2020.9349560"},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Forghani, M., Khachay, M., Firstkov, A., Ramsay, E.: An artificial neural network based ensemble model for predicting antigenic variants: application of reduced amino acid alphabets and word2vec. In: 2022 8th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), pp.\u00a01\u20136. IEEE (2022)","DOI":"10.1109\/ICSPIS56952.2022.10044061"},{"key":"13_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.prevetmed.2021.105318","volume":"190","author":"G Govindaraj","year":"2021","unstructured":"Govindaraj, G., et al.: Foot and mouth disease (fmd) incidence in cattle and buffaloes and its associated farm-level economic costs in endemic India. Prev. Vet. Med. 190, 105318 (2021)","journal-title":"Prev. Vet. Med."},{"issue":"1","key":"13_CR8","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1093\/nar\/27.1.368","volume":"27","author":"S Kawashima","year":"1999","unstructured":"Kawashima, S., Ogata, H., Kanehisa, M.: Aaindex: amino acid index database. Nucleic Acids Res. 27(1), 368\u2013369 (1999)","journal-title":"Nucleic Acids Res."},{"key":"13_CR9","doi-asserted-by":"publisher","unstructured":"Khachay, M.: Committee polyhedral separability: complexity and polynomial approximation. Mach. Learn., 231\u2013251 (2015). https:\/\/doi.org\/10.1007\/s10994-015-5505-0","DOI":"10.1007\/s10994-015-5505-0"},{"issue":"3\u20134","key":"13_CR10","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1016\/j.prevetmed.2013.07.013","volume":"112","author":"TJ Knight-Jones","year":"2013","unstructured":"Knight-Jones, T.J., Rushton, J.: The economic impacts of foot and mouth disease-what are they, how big are they and where do they occur? Prev. Vet. Med. 112(3\u20134), 161\u2013173 (2013)","journal-title":"Prev. Vet. Med."},{"key":"13_CR11","doi-asserted-by":"publisher","first-page":"3503","DOI":"10.1016\/j.csbj.2022.07.001","volume":"20","author":"Y Liang","year":"2022","unstructured":"Liang, Y., et al.: Research progress of reduced amino acid alphabets in protein analysis and prediction. Comput. Struct. Biotechnol. J. 20, 3503\u20133510 (2022)","journal-title":"Comput. Struct. Biotechnol. J."},{"issue":"8","key":"13_CR12","doi-asserted-by":"publisher","first-page":"1307","DOI":"10.1093\/bioinformatics\/btu820","volume":"31","author":"B Liu","year":"2015","unstructured":"Liu, B., Liu, F., Fang, L., Wang, X., Chou, K.C.: repdna: a python package to generate various modes of feature vectors for dna sequences by incorporating user-defined physicochemical properties and sequence-order effects. Bioinformatics 31(8), 1307\u20131309 (2015)","journal-title":"Bioinformatics"},{"issue":"2","key":"13_CR13","doi-asserted-by":"publisher","first-page":"384","DOI":"10.1099\/vir.0.057521-0","volume":"95","author":"AB Ludi","year":"2014","unstructured":"Ludi, A.B., et al.: Antigenic variation of foot-and-mouth disease virus serotype A. J. Gen. Virol. 95(2), 384\u2013392 (2014)","journal-title":"J. Gen. Virol."},{"issue":"7","key":"13_CR14","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1080\/14760584.2018.1492378","volume":"17","author":"M Mahapatra","year":"2018","unstructured":"Mahapatra, M., Parida, S.: Foot and mouth disease vaccine strain selection: current approaches and future perspectives. Expert Rev. Vaccines 17(7), 577\u2013591 (2018)","journal-title":"Expert Rev. Vaccines"},{"issue":"27","key":"13_CR15","doi-asserted-by":"publisher","first-page":"3199","DOI":"10.1016\/j.vaccine.2016.02.057","volume":"34","author":"M Mahapatra","year":"2016","unstructured":"Mahapatra, M., Statham, B., Li, Y., Hammond, J., Paton, D., Parida, S.: Emergence of antigenic variants within serotype a fmdv in the middle east with antigenically critical amino acid substitutions. Vaccine 34(27), 3199\u20133206 (2016)","journal-title":"Vaccine"},{"key":"13_CR16","doi-asserted-by":"crossref","unstructured":"Makau, D.N., Arzt, J., VanderWaal, K.: Machine learning approaches for estimating cross-neutralization potential among fmd serotype o viruses. bioRxiv pp. 2024\u201305 (2024)","DOI":"10.1101\/2024.05.22.594549"},{"key":"13_CR17","unstructured":"Mikolov, T.: Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.37813781 (2013)"},{"issue":"1","key":"13_CR18","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1186\/s12859-023-05232-0","volume":"24","author":"S Musleh","year":"2023","unstructured":"Musleh, S., Islam, M.T., Qureshi, R., Alajez, N.M., Alam, T.: Mslp: mrna subcellular localization predictor based on machine learning techniques. BMC Bioinf. 24(1), 109 (2023)","journal-title":"BMC Bioinf."},{"key":"13_CR19","unstructured":"Ng, P.: dna2vec: consistent vector representations of variable-length k-mers. arXiv preprint arXiv:1701.06279 (2017)"},{"key":"13_CR20","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.680687","volume":"12","author":"M Ostrovsky-Berman","year":"2021","unstructured":"Ostrovsky-Berman, M., Frankel, B., Polak, P., Yaari, G.: Immune2vec: embedding $$B\/T$$ cell receptor sequences in $$\\textbf{R} ^{N}$$ using natural language processing. Front. Immunol. 12, 680687 (2021)","journal-title":"Front. Immunol."},{"issue":"2","key":"13_CR21","doi-asserted-by":"publisher","first-page":"677","DOI":"10.1109\/TCBB.2019.2923396","volume":"18","author":"J Qiu","year":"2019","unstructured":"Qiu, J., et al.: Predicting the antigenic relationship of foot-and-mouth disease virus for vaccine selection through a computational model. IEEE\/ACM Trans. Comput. Biol. Bioinf. 18(2), 677\u2013685 (2019)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf."},{"issue":"7","key":"13_CR22","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0159360","volume":"11","author":"R Reeve","year":"2016","unstructured":"Reeve, R., et al.: Tracking the antigenic evolution of foot-and-mouth disease virus. PLoS ONE 11(7), e0159360 (2016)","journal-title":"PLoS ONE"},{"issue":"1","key":"13_CR23","first-page":"107","volume":"81","author":"MM Rweyemamu","year":"1978","unstructured":"Rweyemamu, M.M., Booth, J.C., Head, M., Pay, T.W.: Microneutralization tests for serological typing and subtyping of foot-and-mouth disease virus strains. Epidemiol. Infect. 81(1), 107\u2013123 (1978)","journal-title":"Epidemiol. Infect."},{"issue":"D1","key":"13_CR24","doi-asserted-by":"crossref","first-page":"D84","DOI":"10.1093\/nar\/gkz899","volume":"48","author":"EW Sayers","year":"2020","unstructured":"Sayers, E.W., Cavanaugh, M., Clark, K., Ostell, J., Pruitt, K.D., Karsch-Mizrachi, I.: Genbank. Nucleic Acids Res. 48(D1), D84\u2013D86 (2020)","journal-title":"Nucleic Acids Res."},{"key":"13_CR25","doi-asserted-by":"crossref","unstructured":"Sonkar, S., Waters, A.E., Baraniuk, R.G.: Attention word embedding. arXiv preprint arXiv:2006.00988 (2020)","DOI":"10.18653\/v1\/2020.coling-main.608"},{"issue":"7","key":"13_CR26","doi-asserted-by":"publisher","first-page":"3022","DOI":"10.1093\/molbev\/msab120","volume":"38","author":"K Tamura","year":"2021","unstructured":"Tamura, K., Stecher, G., Kumar, S.: Mega11: molecular evolutionary genetics analysis version 11. Molec. Biol. Evol. 38(7), 3022\u20133027 (2021). https:\/\/doi.org\/10.1093\/molbev\/msab120","journal-title":"Molec. Biol. Evol."},{"issue":"6","key":"13_CR27","doi-asserted-by":"publisher","first-page":"3497","DOI":"10.1109\/TCBB.2021.3108971","volume":"19","author":"R Yin","year":"2021","unstructured":"Yin, R., Thwin, N.N., Zhuang, P., Lin, Z., Kwoh, C.K.: Iav-cnn: a 2d convolutional neural network model to predict antigenic variants of influenza a virus. IEEE\/ACM Trans. Comput. Biol. Bioinf. 19(6), 3497\u20133506 (2021)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf."},{"issue":"2","key":"13_CR28","doi-asserted-by":"publisher","first-page":"78","DOI":"10.2174\/1389202915999140328162433","volume":"15","author":"R Zhang","year":"2014","unstructured":"Zhang, R., Zhang, C.T.: A brief review: the z-curve theory and its application in genome analysis. Curr. Genom. 15(2), 78\u201394 (2014)","journal-title":"Curr. Genom."},{"key":"13_CR29","unstructured":"Zhou, Z., Ji, Y., Li, W., Dutta, P., Davuluri, R., Liu, H.: Dnabert-2: efficient foundation model and benchmark for multi-species genome. arXiv preprint arXiv:2306.15006 (2023)"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition. ICPR 2024 International Workshops and Challenges"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-87663-9_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T05:14:15Z","timestamp":1746767655000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-87663-9_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031876622","9783031876639"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-87663-9_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"10 May 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kolkata","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","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":"1 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}