The article introduces MEME-ChIP, a web service designed to analyze large, high-quality datasets from transcription factor (TF) ChIP-seq experiments. The service performs five types of analyses: ab initio motif discovery, motif enrichment analysis, motif visualization, binding affinity analysis, and motif identification. It uses two complementary motif discovery algorithms, MEME and DREME, and the AME algorithm for motif enrichment analysis. MEME-ChIP is unique in its ability to handle very large datasets without restrictions on the size or number of uploaded sequences. The service provides a comprehensive view of the binding and regulatory activity of the ChIP-ed TF and its potential regulatory partners. The article also includes a detailed implementation description and an example using SCL (Tal1) ChIP-seq data to demonstrate the functionality of MEME-ChIP.The article introduces MEME-ChIP, a web service designed to analyze large, high-quality datasets from transcription factor (TF) ChIP-seq experiments. The service performs five types of analyses: ab initio motif discovery, motif enrichment analysis, motif visualization, binding affinity analysis, and motif identification. It uses two complementary motif discovery algorithms, MEME and DREME, and the AME algorithm for motif enrichment analysis. MEME-ChIP is unique in its ability to handle very large datasets without restrictions on the size or number of uploaded sequences. The service provides a comprehensive view of the binding and regulatory activity of the ChIP-ed TF and its potential regulatory partners. The article also includes a detailed implementation description and an example using SCL (Tal1) ChIP-seq data to demonstrate the functionality of MEME-ChIP.