The transcription process is the initial step in gene expression and the core of the regulatory mechanism, in which transcription factors control gene expression through interactions with particular DNA sequences. Therefore, identification of transcription factor binding sites (TFBSs) provides theoretical basis for further dissection of transcriptional regulatory mechanisms and disease diagnosis. To address the limitations of current research on TFBSs, a novel symmetric Encoder-Decoder framework is proposed for predicting transcription factor binding signals values at base sites. Our approach utilizes word vectors to encode DNA sequences, followed by encoders that progressively extract feature representations from these sequences. We then employ Gated Recurrent Unit (GRU) to capture the contextual dependencies within the sequences, ultimately using decoders to reconstruct the binding signal values for the DNA sequence sites. In order to access the effectiveness of the proposed symmetric Encoder-Decoder framework, some experiments were conducted on 20 ChIP-seq datasets, and the results show that the proposed novel method outperformers several existing advanced methods.