Identifying repeated factors that occur in a string of letters or common factors that occur in a set of strings represents an important task in computer science and biology. Such patterns are called motifs, and the process of identifying them is called motif extraction. In biology, motif extraction constitutes a fundamental step in understanding regulation of gene expression. State-of-the-art tools for motif extraction have their own constraints. Most of these tools are only designed for single motif extraction, structured motifs additionally allow for distance intervals between their single motif components. Moreover, motif extraction from large-scale datasets-for instance, large-scale ChIP-Seq datasets-cannot be performed by current tools. Other constraints include high time and/or space complexity for identifying long motifs with higher error thresholds.