The international journal “Nucleic Acids Research” (IF=11.5) of Oxford University Press published AnimalTFDB v3.0 (http://bioinfo.life.hust.edu.cn/AnimalTFDB/) online on September 12. Professor An-Yuan Guo is the corresponding author, two Ph.D. students Hui Hu and Ya-Ru Miao are the joint first authors.

Professor An-Yuan Guo’s team built the first version of AnimalTFDB in 2011, which has been maintained and updated for seven years. Three versions of the database were all published on Nucleic Acids Research.

AnimalTFDB is one of the most authoritative resources in the research of transcription factors (TFs) due to the latest, accurate and comprehensive data as well as the convenient web interface. Furthermore, the result of comparison with other related databases shows that AnimalTFDB is the most accurate and reliable animal transcription factor database. Untill now, AnimalTFDB has been visited more than 1 million times by users in more than 60 countries, and it was cited nearly 300 times by many papers including those published on Nature and Cell.

                                                             Figure1 AnimalTFDB3.0 database

In the latest version of AnimalTFDB, the author identified and classified 125,135 TF genes and 80,060 transcription cofactor genes in 97 animal genomes. And the annotation information of the TFs and cofactors includes basic information, gene model, protein functional domain, gene ontology, pathway, protein interaction, ortholog and paralog, gene expression in tissue and disease, etc. Besides, a TF prediction server to identify new TFs from input sequences and a TFBS prediction server to identify TF binding sites in DNA sequences were provided. Due to the extensive use of human transcription factors, the author also built a database named HumanTFDB (http://bioinfo.life.hust.edu.cn/HumanTFDB/).

As known, TFs are special proteins with sequence specific DNA-binding domains (DBDs) that bind target DNA to promote or suppress gene transcription and play key roles in all kinds of biological processes. Thus, the accurate identification, classification and annotation of TFs have always been the focus and basis for studying the function of TFs and TF related processes.