Finding subtle motifs with variable gaps in unaligned DNA sequences

Biologists have determined that the control and regulation of gene expression is primarily determined by relatively short sequences in the region surrounding a gene. These sequences vary in length, position, redundancy, orientation, and bases. Finding these short sequences is a fundamental problem in molecular biology with important applications. Though there exist many different approaches to signal (i.e. short sequence) finding, some new study shows that this problem still leaves plenty of room for improvement. In 2000, Pevzner and Sze proposed the Challenge Problem of motif detection. They reported that most current motif finding algorithms are incapable of detecting the target motifs in their Challenge Problem. In this paper, we show that using an iterative-restart design, our new algorithm can correctly find the target motifs. Furthermore, taking into account the fact that some transcription factors form a dimer or even more complex structures, and transcription process can sometimes involve multiple factors with variable spacers in between, we extend the original problem to an even more challenging one by addressing the issue of combinatorial signals with gaps of variable lengths. To demonstrate the effectiveness of our algorithm, we tested it on a series of the new challenge problem as well as real regulons, and compared it with some current representative motif-finding algorithms.