Locating transcription factor binding sites (motifs) is a key step in understanding gene regulation. Based on Tompas benchmark study, the performance of current de novo motif finders is far from satisfactory (with sensitivity <or=0.222 and precision <or=0.307). The same study also shows that no motif finder performs consistently well over all datasets. Hence, it is not clear which finder one should use for a given dataset. To address this issue, a class of algorithms called ensemble methods have been proposed. Though the existing ensemble methods overall perform better than stand-alone motif finders, the improvement gained is not substantial. Our study reveals that these methods do not fully exploit the information obtained from the results of individual finders, resulting in minor improvement in sensitivity and poor precision.