Primary sequence motifs are often characterized by position-specific score matrices (PSSMs), which are used to generate scores for all possible DNA subsequences to identify potential motifs of various biological significance. The predominant application of PSSMs is the identification of transcription factor binding sites (TFBSs) in the genome. Here by modelling the local sequences as Markov, we assign probabilistic significance to each candidate TFBS with respect to its genomic context...