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Summary: Although the existing works on DNA motif discovery on DNA sequences are plethoric, mechanistic knowledge to infer DNA motifs from protein sequences across multiple DNA-binding domain families without conducting any wet-lab experiments is still lacking. Therefore, the k-spectrum recognition modeling is proposed to address the issues at the highest possible resolutions. The k-spectrum model can capture DNA motif patterns from protein sequences at the resolution in which local sequence context and nucleotide dependency can be taken into account completely. Multiple evaluation metrics are adopted and measured on millions of k-mer binding intensities from 92 proteins across 5 DNA-binding families (i.e., bHLH, bZIP, ETS, Forkhead, and Homeodomain), demonstrating its competitive edges. In addition, it not only can contribute to DNA motif recognition modeling but also can help prioritize the observed or even unobserved binding of single nucleotide variants on transcription factor binding sites in a genome-wide manner. : Genetics; Quantitative Genetics; Bioinformatics; Computational Biology; DNA Motifs Subject Areas: Genetics, Quantitative Genetics, Bioinformatics, Computational Biology, DNA Motifs