Transcription factors (TFs) as key regulators play crucial roles in biological processes. The identification of TF-target regulatory relationships is a key step for revealing functions of TFs and their regulations on gene expression. The accumulated data of chromatin immunoprecipitation sequencing (ChIP-seq) provide great opportunities to discover the TF-target regulations across different conditions. In this study, we constructed a database named hTFtarget, which integrated huge human TF target resources (7190 ChIP-seq samples of 659 TFs and high-confidence binding sites of 699 TFs) and epigenetic modification information to predict accurate TF-target regulations. hTFtarget offers the following functions for users to explore TF-target regulations: 1) browse or search general targets of a query TF across datasets; 2) browse TF-target regulations for a query TF in a specific dataset or tissue; 3) search potential TFs for a given target gene or non-coding RNA; 4) investigate co-association between TFs in cell lines; 5) explore potential co-regulations for given target genes or TFs; 6) predict candidate TF binding sites on given DNA sequences; 7) visualize ChIP-seq peaks for different TFs and conditions in a genome browser. hTFtarget provides a comprehensive, reliable and user-friendly resource for exploring human TF-target regulations, which will be very useful for a wide range of users in the TF and gene expression regulation community. hTFtarget is available at http://bioinfo.life.hust.edu.cn/hTFtarget.
