DNA motifs are short sequences varying from 6 to 25 bp and can be highly variable and degenerated. One major approach for predicting transcription factor (TF) binding is using position weight matrix (PWM) to represent information content of regulatory sites; however, when used as the sole means of identifying binding sites suffers from the limited amount of training data available and a high rate of false-positive predictions. ChIPMotifs program is a de novo motif finding tool developed for ChIP-based high-throughput data, and W-ChIPMotifs is a Web application tool for ChIPMotifs. It composes various ab initio motif discovery tools such as MEME, MaMF, Weeder and optimizes the significance of the detected motifs by using bootstrap re-sampling error estimation and a Fisher test. Using these techniques, we determined a PWM for OCT4 which is similar to canonical OCT4 consensus sequence. In a separate study, we also use de novo motif discovery to suggest that ZNF263 binds to a 24-nt site that differs from the motif predicted by the zinc finger code in several positions.