Backgrounds: Difficulty on identification of transcription factor binding site lies in, compared
with those hundreds or thousands bp background noise sequences, the motif signals with ten to
several tens bp in length are rather short; moreover, the motif instance of a transcription factor is likely
to mutate partially. The TFBS identification has always been a challenge task.
Results: The experimental methods which are widely used in the study on transcription regulation, the
databases that collect information on TFBS, the models that represent TFBS and the TFBS identification
algorithms are introduced and reviewed systematically in this paper.
Conclusion: The regulation mechanism of TFBS in the regulation network is to be further discovered. We insist that the
progress on experiment technology and the insight into the regulation mechanism will definitely bring new life into the
bioinformatics on TFBS. Since deep learning method has manifested the excellent performance on identification of TFBS,
there are good reasons to believe that integrated more up-to-date biological data, the deep learning method will become
the dominant way to study transcription regulation.