Although such a large and dynamic volume of cellular traffic likely requires extensive regulation, proteins are often proposed to localize to the nucleolus simply through high-affinity binding to core nucleolar components [6, 9] . Despite this, numerous disparate reports of short nucleolar targeting sequences in proteins have been published over the past 20 years. Many of these sequences can localize non-nucleolar reporter proteins to the nucleolus when fused to them. In an effort to catalogue and systematically characterize these Nucleolar Localization Sequences (NoLSs), we have recently curated the literature and assembled a human NoLS dataset which we subsequently used to train an artificial neural network computational predictor [10] . The predictor considers the protein sequence and JPred predictions of protein secondary structure [11] . When applied to the entire human proteome, it identified thousands of candidate NoLSs, ten of which were experimentally tested and confirmed to target the nucleolus [10] .