title: AllerTOP v.2--a server for in silico prediction of allergens.
abstract: Allergy is an overreaction by the immune system to a previously encountered, ordinarily harmless substance--typically proteins--resulting in skin rash, swelling of mucous membranes, sneezing or wheezing, or other abnormal conditions. The use of modified proteins is increasingly widespread: their presence in food, commercial products, such as washing powder, and medical therapeutics and diagnostics, makes predicting and identifying potential allergens a crucial societal issue. The prediction of allergens has been explored widely using bioinformatics, with many tools being developed in the last decade; many of these are freely available online. Here, we report a set of novel models for allergen prediction utilizing amino acid E-descriptors, auto- and cross-covariance transformation, and several machine learning methods for classification, including logistic regression (LR), decision tree (DT), naïve Bayes (NB), random forest (RF), multilayer perceptron (MLP) and k nearest neighbours (kNN). The best performing method was kNN with 85.3% accuracy at 5-fold cross-validation. The resulting model has been implemented in a revised version of the AllerTOP server (http://www.ddg-pharmfac.net/AllerTOP).
authors.affiliation: Faculty of Pharmacy, Medical University of Sofia, 2 Dunav st., 1000, Sofia, Bulgaria.
authors.forename: Ivan
authors.initials: I
authors.lastname: Dimitrov
authors.forename: Ivan
authors.initials: I
authors.lastname: Bangov
authors.forename: Darren R
authors.initials: DR
authors.lastname: Flower
authors.forename: Irini
authors.initials: I
authors.lastname: Doytchinova
mesh_terms: D000485:Allergens / Q000009:adverse effects* / Q000737:chemistry* / Q000276:immunology; D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D003661:Decision Support Techniques; D003663:Decision Trees; D006801:Humans; D006967:Hypersensitivity / Q000209:etiology* / Q000276:immunology; D016015:Logistic Models; D011506:Proteins / Q000009:adverse effects* / Q000737:chemistry* / Q000276:immunology; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D013329:Structure-Activity Relationship
chemical_list: D000485:Allergens; D011506:Proteins