In order to address this problem, the DREAM (Dialogue for Reverse Engineering Assessments and Methods) Consortium issued the Epitope-Antibody Recognition (EAR) Specificity Prediction Challenge (Challenge 1). In the experimental work leading to this challenge, 75534 peptides were incubated with commercially available intravenous immunoglobulin (IVIg) fractions. IVIg is a mixture of naturally occurring human antibodies isolated from up to 100000 healthy individuals. From this dataset, high-confidence negative and positive pools of peptides were determined. Training and test datasets were assembled from these peptide pools. The epitope-antibody recognition challenge consists of determining whether each peptide in the test set belongs to the positive or negative set starting from the data of the training set.