{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:43:13Z","timestamp":1776087793956,"version":"3.50.1"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"S6","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2013,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Allergy is a form of hypersensitivity to normally innocuous substances, such as dust, pollen, foods or drugs. Allergens are small antigens that commonly provoke an IgE antibody response. There are two types of bioinformatics-based allergen prediction. The first approach follows FAO\/WHO <jats:italic>Codex alimentarius<\/jats:italic> guidelines and searches for sequence similarity. The second approach is based on identifying conserved allergenicity-related linear motifs. Both approaches assume that allergenicity is a linearly coded property. In the present study, we applied ACC pre-processing to sets of known allergens, developing alignment-independent models for allergen recognition based on the main chemical properties of amino acid sequences.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>A set of 684 food, 1,156 inhalant and 555 toxin allergens was collected from several databases. A set of non-allergens from the same species were selected to mirror the allergen set. The amino acids in the protein sequences were described by three <jats:italic>z<\/jats:italic>-descriptors (<jats:italic>z<\/jats:italic>\n              <jats:sub>\n                <jats:italic>1<\/jats:italic>\n              <\/jats:sub>, <jats:italic>z<\/jats:italic>\n              <jats:sub>\n                <jats:italic>2<\/jats:italic>\n              <\/jats:sub> and <jats:italic>z<\/jats:italic>\n              <jats:sub>\n                <jats:italic>3<\/jats:italic>\n              <\/jats:sub>) and by auto- and cross-covariance (ACC) transformation were converted into uniform vectors. Each protein was presented as a vector of 45 variables. Five machine learning methods for classification were applied in the study to derive models for allergen prediction. The methods were: discriminant analysis by partial least squares (DA-PLS), logistic regression (LR), decision tree (DT), na\u00efve Bayes (NB) and <jats:italic>k<\/jats:italic> nearest neighbours (<jats:italic>k<\/jats:italic> NN). The best performing model was derived by <jats:italic>k<\/jats:italic> NN at <jats:italic>k<\/jats:italic> = 3. It was optimized, cross-validated and implemented in a server named AllerTOP, freely accessible at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/www.pharmfac.net\/allertop\" ext-link-type=\"uri\">http:\/\/www.pharmfac.net\/allertop<\/jats:ext-link>. AllerTOP also predicts the most probable route of exposure. In comparison to other servers for allergen prediction, AllerTOP outperforms them with 94% sensitivity.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>AllerTOP is the first alignment-free server for <jats:italic>in silico<\/jats:italic> prediction of allergens based on the main physicochemical properties of proteins. Significantly, as well allergenicity AllerTOP is able to predict the route of allergen exposure: food, inhalant or toxin.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-14-s6-s4","type":"journal-article","created":{"date-parts":[[2013,4,17]],"date-time":"2013-04-17T11:35:27Z","timestamp":1366198527000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":401,"title":["AllerTOP - a server for in silico prediction of allergens"],"prefix":"10.1186","volume":"14","author":[{"given":"Ivan","family":"Dimitrov","sequence":"first","affiliation":[]},{"given":"Darren R","family":"Flower","sequence":"additional","affiliation":[]},{"given":"Irini","family":"Doytchinova","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2013,4,17]]},"reference":[{"key":"5802_CR1","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1111\/j.0141-9838.2004.00728.x","volume":"26","author":"PJ Cooper","year":"2004","unstructured":"Cooper PJ: Intestinal worms and human allergy. Parasite Immunol. 2004, 26: 455-467. 10.1111\/j.0141-9838.2004.00728.x.","journal-title":"Parasite Immunol"},{"key":"5802_CR2","volume-title":"Immunobiology: the immune system in health and disease","author":"CA Janeway","year":"1999","unstructured":"Janeway CA, Travers P, Walport M, Capra JD: Immunobiology: the immune system in health and disease. 1999, London: Current Biology Publications"},{"key":"5802_CR3","doi-asserted-by":"publisher","first-page":"686","DOI":"10.1136\/bmj.316.7132.686","volume":"316","author":"C Rusznak","year":"1998","unstructured":"Rusznak C, Davies RJ: ABC of allergies. Diagnosing Allergy. BMJ. 1998, 316: 686-689. 10.1136\/bmj.316.7132.686.","journal-title":"BMJ"},{"key":"5802_CR4","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1093\/toxsci\/55.2.235","volume":"55","author":"RDJ Huby","year":"2000","unstructured":"Huby RDJ, Dearman RJ, Kimber I: Why are some proteins allergens. Toxicological Sci. 2000, 55: 235-246. 10.1093\/toxsci\/55.2.235.","journal-title":"Toxicological Sci"},{"key":"5802_CR5","doi-asserted-by":"publisher","first-page":"3256","DOI":"10.1016\/j.molimm.2007.01.019","volume":"44","author":"C Emanuelsson","year":"2007","unstructured":"Emanuelsson C, Spangfort MD: Allergens as eukaryotic proteins lacking bacterial homologues. Mol Immunol. 2007, 44: 3256-3260. 10.1016\/j.molimm.2007.01.019.","journal-title":"Mol Immunol"},{"key":"5802_CR6","volume-title":"Report of a Joint FAO\/WHO Expert Consultation on Allergenicity of Foods Derived from Biotechnology. Rome, Italy","author":"FAO\/WHO Agriculture and Consumer Protection","year":"2001","unstructured":"FAO\/WHO Agriculture and Consumer Protection: Evaluation of Allergenicity of Genetically Modified Foods. Report of a Joint FAO\/WHO Expert Consultation on Allergenicity of Foods Derived from Biotechnology. Rome, Italy. 2001"},{"key":"5802_CR7","volume-title":"Joint FAO\/WHO Food Standards Programme. Rome, Italy","author":"FAO\/WHO Codex Alimentarius Commission","year":"2003","unstructured":"FAO\/WHO Codex Alimentarius Commission: Codex Principles and Guidelines on Foods Derived from Biotechnology. Joint FAO\/WHO Food Standards Programme. Rome, Italy. 2003"},{"key":"5802_CR8","doi-asserted-by":"publisher","first-page":"1083","DOI":"10.1034\/j.1398-9995.2003.00224.x","volume":"58","author":"V Brusic","year":"2003","unstructured":"Brusic V, Petrovsky N, Gendel SM, Millot M, Gigonzac O, Stelman SJ: Computational tools for the study of allergens. Allergy. 2003, 58: 1083-1092. 10.1034\/j.1398-9995.2003.00224.x.","journal-title":"Allergy"},{"key":"5802_CR9","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1093\/nar\/gkg010","volume":"31","author":"O Ivanciuc","year":"2003","unstructured":"Ivanciuc O, Schein CH, Braun W: SDAP: database and computational tools for allergenic proteins. Nucleic Acids Res. 2003, 31: 359-362. 10.1093\/nar\/gkg010.","journal-title":"Nucleic Acids Res"},{"key":"5802_CR10","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1186\/1471-2105-5-133","volume":"5","author":"MWEJ Fiers","year":"2004","unstructured":"Fiers MWEJ, Kleter GA, Nijland H, Peijnenburg AACM, Nap JP, vanHam RCHJ: Allermatch, a webtool for the prediction of potential allergenicity according to current fao\/who codex alimentarius guidelines. BMC Bioinformatics. 2004, 5: 133-10.1186\/1471-2105-5-133.","journal-title":"BMC Bioinformatics"},{"key":"5802_CR11","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1093\/bioinformatics\/btl621","volume":"23","author":"ZH Zhang","year":"2007","unstructured":"Zhang ZH, Koh JL, Zhang GL, Choo KH, Tammi MT, Tong JC: AllerTool: a web server for predicting allergenicity and allergic cross-reactivity in proteins. Bioinformatics. 2007, 23: 504-506. 10.1093\/bioinformatics\/btl621.","journal-title":"Bioinformatics"},{"key":"5802_CR12","doi-asserted-by":"crossref","first-page":"1141","DOI":"10.1096\/fj.02-1052fje","volume":"17","author":"MB Stadler","year":"2003","unstructured":"Stadler MB, Stadler BM: Allergenicity prediction by protein sequence. FASEB J. 2003, 17: 1141-1143.","journal-title":"FASEB J"},{"key":"5802_CR13","doi-asserted-by":"publisher","first-page":"2572","DOI":"10.1093\/bioinformatics\/bth286","volume":"20","author":"KB Li","year":"2004","unstructured":"Li KB, Isaac P, Krishnan P: Predicting allergenic proteins using wavelet transform. Bioinformatics. 2004, 20: 2572-2578. 10.1093\/bioinformatics\/bth286.","journal-title":"Bioinformatics"},{"key":"5802_CR14","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1093\/bioinformatics\/bth477","volume":"21","author":"AK Bj\u00f6rklund","year":"2005","unstructured":"Bj\u00f6rklund AK, Soeria-Atmadja D, Zorzet A, Hammerling U, Gustafsson MG: Supervised identification of allergen-representative peptides for in silico detection of potentially allergenic proteins. Bioinformatics. 2005, 21: 39-50. 10.1093\/bioinformatics\/bth477.","journal-title":"Bioinformatics"},{"key":"5802_CR15","doi-asserted-by":"publisher","first-page":"W202","DOI":"10.1093\/nar\/gkl343","volume":"34","author":"S Saha","year":"2006","unstructured":"Saha S, Raghava GPS: AlgPred: prediction of allergenic proteins and mapping of IgE epitopes. Nucleic Acids Res. 2006, 34: W202-W209. 10.1093\/nar\/gkl343.","journal-title":"Nucleic Acids Res"},{"key":"5802_CR16","doi-asserted-by":"publisher","first-page":"4201","DOI":"10.1093\/bioinformatics\/bti700","volume":"21","author":"R Furmonaviciene","year":"2005","unstructured":"Furmonaviciene R, Sutton BJ, Glaser F, Laughton CA, Jones N, Sewell HF, Shakib F: An attempt to define allergen-specific molecular surface features: a bioinformatic approach. Bioinformatics. 2005, 21: 4201-4204. 10.1093\/bioinformatics\/bti700.","journal-title":"Bioinformatics"},{"key":"5802_CR17","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1038\/nri1372","volume":"4","author":"SY Seong","year":"2004","unstructured":"Seong SY, Matzinger P: Hydrophobicity: an ancient damage-associated molecular pattern that initiates innate immune responses. Nat Rev Immunol. 2004, 4: 469-10.1038\/nri1372.","journal-title":"Nat Rev Immunol"},{"key":"5802_CR18","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1016\/0003-2670(93)80437-P","volume":"277","author":"S Wold","year":"1993","unstructured":"Wold S, Jonsson J, Sj\u00f6str\u00f6m M, Sandberg M, R\u00e4nnar S: DNA and Peptide Sequences and Chemical Processes Multivariately Modelled by Principal Components Analysis and Partial Least Squares Projections to Latent Structures. Anal Chim Acta. 1993, 277: 239-253. 10.1016\/0003-2670(93)80437-P.","journal-title":"Anal Chim Acta"},{"key":"5802_CR19","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/S0169-7439(98)00062-8","volume":"42","author":"PM Andersson","year":"1998","unstructured":"Andersson PM, Sj\u00f6str\u00f6m M, Lundstedt T: Preprocessing peptide sequences for multivariate sequence-property analysis. Chemometr Intell Lab. 1998, 42: 41-50. 10.1016\/S0169-7439(98)00062-8.","journal-title":"Chemometr Intell Lab"},{"key":"5802_CR20","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1002\/1521-3838(200006)19:3<264::AID-QSAR264>3.0.CO;2-A","volume":"19","author":"\u00c5 Nystr\u00f6m","year":"2000","unstructured":"Nystr\u00f6m \u00c5, Andersson PM, Lundstedt T: Multivariate data analysis of topographically modified \u00e1-melanotropin analoques using auto and cross auto covariances (ACC). Quant Struct-Act Relat. 2000, 19: 264-269. 10.1002\/1521-3838(200006)19:3<264::AID-QSAR264>3.0.CO;2-A.","journal-title":"Quant Struct-Act Relat"},{"key":"5802_CR21","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1110\/ps.2500102","volume":"11","author":"M Lapinsh","year":"2002","unstructured":"Lapinsh M, Gutcaits A, Prusis P, Post C, Lundstedt T, Wikberg JES: Classification of G-protein coupled receptors by alignment-independent extraction of principal chemical properties of primary amino acid sequences. Protein Sci. 2002, 11: 795-805. 10.1110\/ps.2500102.","journal-title":"Protein Sci"},{"key":"5802_CR22","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1186\/1471-2105-8-4","volume":"8","author":"IA Doytchinova","year":"2007","unstructured":"Doytchinova IA, Flower DR: VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics. 2007, 8: 4-10.1186\/1471-2105-8-4.","journal-title":"BMC Bioinformatics"},{"key":"5802_CR23","doi-asserted-by":"publisher","first-page":"1126","DOI":"10.1021\/jm00390a003","volume":"30","author":"S Hellberg","year":"1987","unstructured":"Hellberg S, Sj\u00f6str\u00f6m M, Skagerberg B, Wold S: Peptide quantitative structure-activity relationships, a multivariate approach. J Med Chem. 1987, 30: 1126-1135. 10.1021\/jm00390a003.","journal-title":"J Med Chem"},{"key":"5802_CR24","doi-asserted-by":"publisher","first-page":"e5861","DOI":"10.1371\/journal.pone.0005861","volume":"4","author":"HC Muh","year":"2009","unstructured":"Muh HC, Tong JC, Tammi MT: AllerHunter: A SVM-pairwise system for assessment of allergenicity and allergic cross-reactivity in proteins. PLoS ONE. 2009, 4: e5861-10.1371\/journal.pone.0005861.","journal-title":"PLoS ONE"},{"key":"5802_CR25","first-page":"525","volume":"2","author":"A Zorzet","year":"2002","unstructured":"Zorzet A, Gustafsson M, Hammerling U: Prediction of food protein allergenicity: A bio-informatic learning systems approach. In Silico Biol. 2002, 2: 525-534.","journal-title":"In Silico Biol"},{"key":"5802_CR26","unstructured":"SIMCA 8.0. Umetrics UK Ltd, Wokingham Road, RG42 1PL, Bracknell, UK"},{"key":"5802_CR27","doi-asserted-by":"publisher","first-page":"1422","DOI":"10.1093\/bioinformatics\/btp163","volume":"25","author":"PJ Cock","year":"2009","unstructured":"Cock PJ, Antao T, Chang JT, Chapman BA, Cox CJ, Dalke A, Friedberg I, Hamelryck T, Kauff F, Wilczynski B, de Hoon MJ: Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics. 2009, 25: 1422-1423. 10.1093\/bioinformatics\/btp163.","journal-title":"Bioinformatics"},{"key":"5802_CR28","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1145\/1656274.1656278","volume":"11","author":"M Hall","year":"2009","unstructured":"Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH: The WEKA data mining software: an update. SIGKDD Explorations. 2009, 11: 10-18. 10.1145\/1656274.1656278.","journal-title":"SIGKDD Explorations"},{"key":"5802_CR29","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.1016\/S0031-3203(96)00142-2","volume":"30","author":"AP Bradley","year":"1997","unstructured":"Bradley AP: The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition. 1997, 30: 1145-1159. 10.1016\/S0031-3203(96)00142-2.","journal-title":"Pattern Recognition"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-14-S6-S4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T23:28:56Z","timestamp":1630538936000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/1471-2105-14-S6-S4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,4]]},"references-count":29,"journal-issue":{"issue":"S6","published-print":{"date-parts":[[2013,4]]}},"alternative-id":["5802"],"URL":"https:\/\/doi.org\/10.1186\/1471-2105-14-s6-s4","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,4]]},"assertion":[{"value":"17 April 2013","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"S4"}}