{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T22:33:46Z","timestamp":1778884426484,"version":"3.51.4"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T00:00:00Z","timestamp":1736121600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T00:00:00Z","timestamp":1736121600000},"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":["Netw Model Anal Health Inform Bioinforma"],"DOI":"10.1007\/s13721-024-00498-7","type":"journal-article","created":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T18:30:00Z","timestamp":1736188200000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Type-2 fuzzy support vector machine model for conformational epitope prediction"],"prefix":"10.1007","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5310-1345","authenticated-orcid":false,"given":"Chhaya","family":"Singh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neeraj","family":"Jain","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neeru","family":"Adlakha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kamal Raj","family":"Pardasani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,6]]},"reference":[{"key":"498_CR1","unstructured":"Runte F, Renner IV P, Hoppe M (2019) Kuby immunology"},{"issue":"3","key":"498_CR2","doi-asserted-by":"publisher","first-page":"738","DOI":"10.1016\/j.jaci.2019.02.023","volume":"144","author":"H Sharif","year":"2019","unstructured":"Sharif H, Singh I, Kouser L, M\u00f6sges R, Bonny M-A, Karamani A, Parkin RV, Bovy N, Kishore U, Robb A et al (2019) Immunologic mechanisms of a short-course of lolium perenne peptide immunotherapy: a randomized, double-blind, placebo-controlled trial. J. Allergy Clin Immunol 144(3):738\u2013749","journal-title":"J. Allergy Clin Immunol"},{"issue":"16","key":"498_CR3","doi-asserted-by":"publisher","first-page":"5315","DOI":"10.1021\/acs.jctc.3c00513","volume":"19","author":"F Guarra","year":"2023","unstructured":"Guarra F, Colombo G (2023) Computational methods in immunology and vaccinology: Design and development of antibodies and immunogens. J Chem Theory Comput 19(16):5315\u20135333","journal-title":"J Chem Theory Comput"},{"key":"498_CR4","doi-asserted-by":"crossref","unstructured":"Bakkouri I, Afdel K (2018) Convolutional neural-adaptive networks for melanoma recognition. In: Image and Signal Processing: 8th International Conference, ICISP 2018, Cherbourg, France, July 2-4, 2018, Proceedings 8, pp 453\u2013460. Springer","DOI":"10.1007\/978-3-319-94211-7_49"},{"issue":"6","key":"498_CR5","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1080\/08830185.2022.2079642","volume":"42","author":"W Gong","year":"2023","unstructured":"Gong W, Parkkila S, Wu X, Aspatwar A (2023) Sars-cov-2 variants and covid-19 vaccines: current challenges and future strategies. Int Rev Immunol 42(6):393\u2013414","journal-title":"Int Rev Immunol"},{"key":"498_CR6","doi-asserted-by":"crossref","unstructured":"Owen JA, Punt J, Stranford SA, Jones PP (2013) Kuby immunology 27. WH Freeman, New York","DOI":"10.3917\/dunod.owen.2014.01.0027"},{"issue":"1","key":"498_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s13721-015-0109-y","volume":"5","author":"C Singh","year":"2016","unstructured":"Singh C, Adlakha N (2016) Scoring function-based soft support vector machine model for prediction of patches containing conformational epitope. Netw Model Anal Health Inform Bioinform 5(1):1\u20136","journal-title":"Netw Model Anal Health Inform Bioinform"},{"issue":"2","key":"498_CR8","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1007\/s005210170010","volume":"10","author":"L Cao","year":"2001","unstructured":"Cao L, Tay FE (2001) Financial forecasting using support vector machines. Neural Comput Appl 10(2):184\u2013192","journal-title":"Neural Comput Appl"},{"issue":"1","key":"498_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1745-7580-2-2","volume":"2","author":"JEP Larsen","year":"2006","unstructured":"Larsen JEP, Lund O, Nielsen M (2006) Improved method for predicting linear b-cell epitopes. Immunome Res 2(1):1","journal-title":"Immunome Res"},{"issue":"3","key":"498_CR10","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1016\/0263-7855(93)80074-2","volume":"11","author":"J Pellequer","year":"1993","unstructured":"Pellequer J, Westhof E (1993) Preditop: a program for antigenicity prediction. J Mol Graph 11(3):204\u2013210","journal-title":"J Mol Graph"},{"issue":"1","key":"498_CR11","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1002\/prot.21078","volume":"65","author":"S Saha","year":"2006","unstructured":"Saha S, Raghava G (2006) Prediction: of continuous b-cell epitopes in an antigen using recurrent neural network. Proteins: Struct, Funct, Bioinf 65(1):40\u201348","journal-title":"Proteins: Struct, Funct, Bioinf"},{"issue":"4","key":"498_CR12","first-page":"1","volume":"11","author":"LJ Wee","year":"2010","unstructured":"Wee LJ, Simarmata D, Kam Y-W, Ng LF, Tong JC (2010) Svm-based prediction of linear b-cell epitopes using bayes feature extraction. BMC Genom 11(4):1","journal-title":"BMC Genom"},{"issue":"3","key":"498_CR13","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1093\/protein\/gzn075","volume":"22","author":"MJ Sweredoski","year":"2009","unstructured":"Sweredoski MJ, Baldi P (2009) Cobepro: a novel system for predicting continuous b-cell epitopes. Protein Eng Des Sel 22(3):113\u2013120","journal-title":"Protein Eng Des Sel"},{"issue":"1","key":"498_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2105-12-251","volume":"12","author":"Y Wang","year":"2011","unstructured":"Wang Y, Wu W, Negre NN, White KP, Li C, Shah PK (2011) Determinants of antigenicity and specificity in immune response for protein sequences. BMC Bioinform 12(1):1","journal-title":"BMC Bioinform"},{"issue":"6","key":"498_CR15","doi-asserted-by":"publisher","first-page":"40104","DOI":"10.1371\/journal.pone.0040104","volume":"7","author":"J Gao","year":"2012","unstructured":"Gao J, Faraggi E, Zhou Y, Ruan J, Kurgan L (2012) Best: improved prediction of b-cell epitopes from antigen sequences. PLoS One 7(6):40104","journal-title":"PLoS One"},{"key":"498_CR16","doi-asserted-by":"publisher","first-page":"1695","DOI":"10.3389\/fimmu.2018.01695","volume":"9","author":"B Manavalan","year":"2018","unstructured":"Manavalan B, Govindaraj RG, Shin TH, Kim MO, Lee G (2018) ibce-el: a new ensemble learning framework for improved linear b-cell epitope prediction. Front Immunol 9:1695","journal-title":"Front Immunol"},{"issue":"10","key":"498_CR17","doi-asserted-by":"publisher","first-page":"648","DOI":"10.1089\/omi.2015.0095","volume":"19","author":"V Saravanan","year":"2015","unstructured":"Saravanan V, Gautham N (2015) Harnessing computational biology for exact linear b-cell epitope prediction: a novel amino acid composition-based feature descriptor. OMICS 19(10):648\u2013658","journal-title":"OMICS"},{"issue":"suppl 2","key":"498_CR18","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1093\/nar\/gki460","volume":"33","author":"U Kulkarni-Kale","year":"2005","unstructured":"Kulkarni-Kale U, Bhosle S, Kolaskar AS (2005) Cep: a conformational epitope prediction server. Nucleic Acids Res 33(suppl 2):168\u2013171","journal-title":"Nucleic Acids Res"},{"issue":"11","key":"498_CR19","doi-asserted-by":"publisher","first-page":"2558","DOI":"10.1110\/ps.062405906","volume":"15","author":"P Haste Andersen","year":"2006","unstructured":"Haste Andersen P, Nielsen M, Lund O (2006) Prediction of residues in discontinuous b-cell epitopes using protein 3d structures. Protein Sci 15(11):2558\u20132567","journal-title":"Protein Sci"},{"issue":"12","key":"498_CR20","doi-asserted-by":"publisher","first-page":"1459","DOI":"10.1093\/bioinformatics\/btn199","volume":"24","author":"MJ Sweredoski","year":"2008","unstructured":"Sweredoski MJ, Baldi P (2008) Pepito: improved discontinuous b-cell epitope prediction using multiple distance thresholds and half sphere exposure. Bioinformatics 24(12):1459\u20131460","journal-title":"Bioinformatics"},{"issue":"1","key":"498_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2105-9-514","volume":"9","author":"J Ponomarenko","year":"2008","unstructured":"Ponomarenko J, Bui H-H, Li W, Fusseder N, Bourne PE, Sette A, Peters B (2008) Ellipro: a new structure-based tool for the prediction of antibody epitopes. BMC Bioinform 9(1):1","journal-title":"BMC Bioinform"},{"issue":"1","key":"498_CR22","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1002\/cpbi.3","volume":"54","author":"B Webb","year":"2016","unstructured":"Webb B, Sali A (2016) Comparative protein structure modeling using modeller. Curr Protoc Bioinform 54(1):5\u20136","journal-title":"Curr Protoc Bioinform"},{"key":"498_CR23","unstructured":"Team J Jmol: an open-source Java viewer for chemical structures in 3D. http:\/\/www.jmol.org\/. Accessed 25 Feb 2022"},{"issue":"W1","key":"498_CR24","doi-asserted-by":"publisher","first-page":"388","DOI":"10.1093\/nar\/gkz413","volume":"47","author":"C Zhou","year":"2019","unstructured":"Zhou C, Chen Z, Zhang L, Yan D, Mao T, Tang K, Qiu T, Cao Z (2019) Seppa 3.0-enhanced spatial epitope prediction enabling glycoprotein antigens. Nucleic Acids Res 47(W1):388\u2013394","journal-title":"Nucleic Acids Res"},{"issue":"W1","key":"498_CR25","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1093\/nar\/gku395","volume":"42","author":"T Qi","year":"2014","unstructured":"Qi T, Qiu T, Zhang Q, Tang K, Fan Y, Qiu J, Wu D, Zhang W, Chen Y, Gao J et al (2014) Seppa 2.0-more refined server to predict spatial epitope considering species of immune host and subcellular localization of protein antigen. Nucleic Acids Res 42(W1):59\u201363","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"498_CR26","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1186\/s12859-014-0414-y","volume":"15","author":"Y Lian","year":"2014","unstructured":"Lian Y, Ge M, Pan X-M (2014) Epmlr: sequence-based linear b-cell epitope prediction method using multiple linear regression. BMC Bioinform 15(1):414","journal-title":"BMC Bioinform"},{"issue":"8","key":"498_CR27","doi-asserted-by":"publisher","first-page":"1313","DOI":"10.1093\/bioinformatics\/btu790","volume":"31","author":"I Sela-Culang","year":"2015","unstructured":"Sela-Culang I, Ashkenazi S, Peters B, Ofran Y (2015) Pease: predicting b-cell epitopes utilizing antibody sequence. Bioinformatics 31(8):1313\u20131315","journal-title":"Bioinformatics"},{"issue":"W1","key":"498_CR28","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1093\/nar\/gku318","volume":"42","author":"G-Y Chuang","year":"2014","unstructured":"Chuang G-Y, Liou D, Kwong PD, Georgiev IS (2014) Nep: web server for epitope prediction based on antibody neutralization of viral strains with diverse sequences. Nucleic Acids Res 42(W1):64\u201371","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"498_CR29","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1186\/1471-2105-10-302","volume":"10","author":"S Liang","year":"2009","unstructured":"Liang S, Zheng D, Zhang C, Zacharias M (2009) Prediction of antigenic epitopes on protein surfaces by consensus scoring. BMC Bioinform 10(1):302","journal-title":"BMC Bioinform"},{"issue":"1","key":"498_CR30","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1186\/1471-2105-11-381","volume":"11","author":"S Liang","year":"2010","unstructured":"Liang S, Zheng D, Standley DM, Yao B, Zacharias M, Zhang C (2010) Epsvr and epmeta: prediction of antigenic epitopes using support vector regression and multiple server results. BMC Bioinform 11(1):381","journal-title":"BMC Bioinform"},{"issue":"W1","key":"498_CR31","doi-asserted-by":"publisher","first-page":"528","DOI":"10.1093\/nar\/gkad427","volume":"51","author":"T Qiu","year":"2023","unstructured":"Qiu T, Zhang L, Chen Z, Wang Y, Mao T, Wang C, Cun Y, Zheng G, Yan D, Zhou M et al (2023) Seppa-mab: spatial epitope prediction of protein antigens for mabs. Nucleic Acids Res 51(W1):528\u2013534","journal-title":"Nucleic Acids Res"},{"key":"498_CR32","doi-asserted-by":"crossref","unstructured":"Ivanisenko NV, Shashkova TI, Shevtsov A, Sindeeva M, Umerenkov D, Kardymon O (2024) Sema 2.0: web-platform for b-cell conformational epitopes prediction using artificial intelligence. Nucleic Acids Res 386","DOI":"10.1093\/nar\/gkae386"},{"key":"498_CR33","doi-asserted-by":"crossref","unstructured":"Bakkouri I, Bakkouri S (2024) 2mgas-net: multi-level multi-scale gated attentional squeezed network for polyp segmentation. Signal, Image Video Process :1\u201310","DOI":"10.1007\/s11760-024-03240-y"},{"issue":"1","key":"498_CR34","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1093\/bib\/bbac567","volume":"24","author":"G Cia","year":"2023","unstructured":"Cia G, Pucci F, Rooman M (2023) Critical review of conformational b-cell epitope prediction methods. Brief Bioinform 24(1):567","journal-title":"Brief Bioinform"},{"issue":"10","key":"498_CR35","doi-asserted-by":"publisher","first-page":"5434","DOI":"10.3390\/ijms25105434","volume":"25","author":"D Li","year":"2024","unstructured":"Li D, Pucci F, Rooman M (2024) Prediction of paratope-epitope pairs using convolutional neural networks. Int J Mol Sci 25(10):5434","journal-title":"Int J Mol Sci"},{"issue":"9","key":"498_CR36","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1007\/s13205-023-03716-7","volume":"13","author":"P Angaitkar","year":"2023","unstructured":"Angaitkar P, Janghel RR, Sahu TP (2023) Dl-tcnn: deep learning-based temporal convolutional neural network for prediction of conformational b-cell epitopes. 3 Biotech 13(9):297","journal-title":"3 Biotech"},{"key":"498_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2024.108083","volume":"170","author":"N Kumar","year":"2024","unstructured":"Kumar N, Tripathi S, Sharma N, Patiyal S, Devi NL, Raghava GP (2024) A method for predicting linear and conformational b-cell epitopes in an antigen from its primary sequence. Comput Biol Med 170:108083","journal-title":"Comput Biol Med"},{"issue":"Suppl 17","key":"498_CR38","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1186\/1471-2105-13-S17-S20","volume":"13","author":"L Zhao","year":"2012","unstructured":"Zhao L, Wong L, Lu L, Hoi SC, Li J (2012) B-cell epitope prediction through a graph model. BMC Bioinform 13(Suppl 17):20","journal-title":"BMC Bioinform"},{"key":"498_CR39","unstructured":"George JK, Bo Y (2008) Fuzzy sets and fuzzy logic, theory and applications"},{"issue":"2","key":"498_CR40","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1016\/S0165-0114(02)00272-5","volume":"138","author":"T-P Hong","year":"2003","unstructured":"Hong T-P, Lin K-Y, Wang S-L (2003) Fuzzy data mining for interesting generalized association rules. Fuzzy Sets Syst 138(2):255\u2013269","journal-title":"Fuzzy Sets Syst"},{"issue":"11","key":"498_CR41","doi-asserted-by":"publisher","first-page":"2065","DOI":"10.1007\/s00500-013-1122-7","volume":"17","author":"M Ha","year":"2013","unstructured":"Ha M, Yang Y, Wang C (2013) A new support vector machine based on type-2 fuzzy samples. Soft Comput 17(11):2065\u20132074","journal-title":"Soft Comput"},{"issue":"1","key":"498_CR42","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1093\/nar\/28.1.235","volume":"28","author":"HM Berman","year":"2000","unstructured":"Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28(1):235\u2013242","journal-title":"Nucleic Acids Res"},{"key":"498_CR43","doi-asserted-by":"crossref","unstructured":"Refaeilzadeh P, Tang L, Liu H (2009) Cross-validation. In: Encyclopedia of database systems, pp. 532\u2013538. Springer, Berlin","DOI":"10.1007\/978-0-387-39940-9_565"},{"issue":"1","key":"498_CR44","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13040-021-00244-z","volume":"14","author":"D Chicco","year":"2021","unstructured":"Chicco D, T\u00f6tsch N, Jurman G (2021) The matthews correlation coefficient (mcc) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation. BioData Mining 14(1):1\u201322","journal-title":"BioData Mining"},{"issue":"02","key":"498_CR45","doi-asserted-by":"publisher","first-page":"2340028","DOI":"10.1142\/S0218348X23400285","volume":"31","author":"R Zhang","year":"2023","unstructured":"Zhang R, Shah NA, El-Zahar ER, Akg\u00fcl A, Chung JD (2023) Numerical analysis of fractional-order emden-fowler equations using modified variational iteration method. Fractals 31(02):2340028","journal-title":"Fractals"},{"issue":"4","key":"498_CR46","first-page":"1","volume":"13","author":"M Vihinen","year":"2012","unstructured":"Vihinen M (2012) How to evaluate performance of prediction methods? measures and their interpretation in variation effect analysis. BMC Genom 13(4):1","journal-title":"BMC Genom"},{"issue":"02","key":"498_CR47","doi-asserted-by":"publisher","first-page":"2340023","DOI":"10.1142\/S0218348X23400236","volume":"31","author":"N Mehmood","year":"2023","unstructured":"Mehmood N, Abbas A, Akg\u00fcl A, Abdeljawad T, Alqudah MA (2023) Existence and stability results for coupled system of fractional differential equations involving ab-caputo derivative. Fractals 31(02):2340023","journal-title":"Fractals"},{"key":"498_CR48","doi-asserted-by":"crossref","unstructured":"Sokolova M, Japkowicz N, Szpakowicz S (2006) Beyond accuracy, f-score and roc: a family of discriminant measures for performance evaluation. In: Australasian Joint Conference on Artificial Intelligence. Springer, Berlin, pp 1015\u20131021","DOI":"10.1007\/11941439_114"},{"issue":"6","key":"498_CR49","doi-asserted-by":"publisher","first-page":"705","DOI":"10.1007\/s42979-023-02091-7","volume":"4","author":"C Singh","year":"2023","unstructured":"Singh C, Adlakha N, Pardasani KR (2023) Fuzzy deep learning model for prediction of conformational epitope. SN Comput Sci 4(6):705","journal-title":"SN Comput Sci"},{"issue":"4","key":"498_CR50","doi-asserted-by":"publisher","first-page":"62249","DOI":"10.1371\/journal.pone.0062249","volume":"8","author":"B Yao","year":"2013","unstructured":"Yao B, Zheng D, Liang S, Zhang C (2013) Conformational b-cell epitope prediction on antigen protein structures: a review of current algorithms and comparison with common binding site prediction methods. PLoS One 8(4):62249","journal-title":"PLoS One"}],"container-title":["Network Modeling Analysis in Health Informatics and Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13721-024-00498-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13721-024-00498-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13721-024-00498-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T20:09:00Z","timestamp":1736194140000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13721-024-00498-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,6]]},"references-count":50,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["498"],"URL":"https:\/\/doi.org\/10.1007\/s13721-024-00498-7","relation":{},"ISSN":["2192-6670"],"issn-type":[{"value":"2192-6670","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,6]]},"assertion":[{"value":"5 May 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 November 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 December 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 January 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"On behalf of all authors, the corresponding author states that there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"4"}}