Scope and method of study. Unraveling the mechanisms that regulate the expression of genes is a major challenge in biology. An important task in this challenge is to identify regulatory elements, especially the binding sites in deoxyribonucleic acid (DNA) for transcription factors. These binding sites are short DNA segments which are called motifs. Given a set of DNA sequences (promoter region), the motif finding problem is the task of detecting overrepresented motifs that are good candidates for being transcription factor binding sites. Co-regulated genes are known to share some similarities in their regulatory mechanism, possibly at transcriptional level, their promoter regions might contain some common motifs that are binding sites for transcriptional regulators. In recent years, due to combined efforts of computer scientists and molecular biologists several algorithms have been developed for finding DNA motifs. The current study is a survey of these motif finding algorithms. We present some relevant information from biology, then we present a list of motif finding algorithms and describe some of these algorithms in detail, next we present some results that have been obtained in the literature using these algorithms, then we present performance comparisons of some of these algorithms and finally we present a discussion on the motif finding algorithms.

Findings and conclusions. A survey of the motif finding algorithms in the current study shows that a sensible approach to detect regulatory elements is to search for statistically overrepresented motifs in the promoter region of a set of co-regulated genes. The weak point of the currently available motif finding algorithms is that they tend to be sensitive to the noise. Noise is due to the presence of upstream sequences in the data set that do not contain the motif. All the algorithms studied were able to correctly detect the motifs that have been previously detected by laboratory experimental approaches. In addition, some algorithms were able to find novel motifs. However, most of these motif finding algorithms have been shown to work successfully in yeast and other lower organisms, but perform significantly worse in higher organisms. We conclude that although the biology of the regulatory mechanism is still poorly understood, motif discovery algorithm should include most available biological information. Instead of relying on a single motif finding tool, biologists should use a few complementary tools in combination and pursue the top few predicted motifs of each rather than the single most significant motif.