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Creators/Authors contains: "Hossein Saghaian, Pavel Skums"

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  1. (, Lecture notes in bioinformatics)
    Phage display technique has a multitude of applications such as epitope mapping, organ targeting, therapeutic antibody engineering and vaccine design. One area of particular importance is the detection of cancers in early stages, where the discovery of binding motifs and epitopes is critical. While several techniques exist to characterize phages, Next Generation Sequencing (NGS) stands out for its ability to provide detailed insights into antibody binding sites on antigens. However, when dealing with NGS data, identifying regulatory motifs poses significant challenges. Existing methods often lack scalability for large datasets, rely on prior knowledge about the number of motifs, and exhibit low accuracy. In this paper, we present a novel approach for identifying regulatory motifs in NGS data. Our method leverages results from graph theory to overcome the limitations of existing techniques. 
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