The truly non-expert user has the option of using a set of default settings. Using these settings, the data is preprocessed using a linear transformation to make the data fall in the range from 0 to 1, and the NN-align method is trained using five-fold crossvalidation. For each cross validation partition five networks, each initiated from different initial configurations, are trained with 3 hidden neurons. The only critical parameter that the user is required to specify is the motif length. The value used for this parameter is specific to each problem and the user is recommended to define a motif length (or an interval of motif length) that is relevant to the biological problem investigated by the peptide data. The default settings will in most cases allow the user to obtain a first impression of the motif contained in the data, and achieve a prediction method that allows the user to make prospective studies on uncharacterized proteins/peptides. The more experienced user has several advanced options to customize the training. For details on these options refer to Materials and Methods section, or the help section of the web-server.