Iodine

Background

Transcription financier binding situation (TFBS) motifs can be accurately represented by position frequency matrices (PFM) or other synonymous forms. We often desperate straits to contrast TFBS motifs using their PFMs in discipline to search for equivalent motifs in a pattern database, or assemble motifs according to their binding leaning. The best part of prevailing methods for subject likeness incorporate a similarity metric for column-to-column match and a method to bump into uncover the optimal predication alignment intermediary the two compared motifs. In some applications, alignment-free methods might be preferred; however, few such methods with high preciseness be subjected to been described.

Methodology/Principal Findings

Here we report a novel alignment-free method for quantifying the similarity of motifs using their PFMs by converting PFMs into k-mer vectors. The motifs could then be compared by measuring the similarity middle their corresponding k-mer vectors.

Conclusions/Significance

We display that our method in imprecise achieves correspond to effectuation or outperforms the existing methods for clustering motifs according to their binding liking and identifying nearly the same motifs of transcription factors of the unvarying progeny.

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