TRANSFAC: an integrated system for gene expression regulation

Abstract

TRANSFAC is a database on transcription factors, their genomic binding sites and DNA-binding profiles (http://transfac.gbf.de/TRANSFAC/). Its content has been enhanced, in particular by information about training sequences used for the construction of nucleotide matrices as well as by data on plant sites and factors. Moreover, TRANSFAC has been extended by two new modules: PathoDB provides data on pathologically relevant mutations in regulatory regions and transcription factor genes, whereas S/MARt DB compiles features of scaffold/matrix attached regions (S/MARs) and the proteins binding to them. Additionally, the databases TRANSPATH, about signal transduction, and CYTOMER, about organs and cell types, have been extended and are increasingly integrated with the TRANSFAC data sources.

Optimized filtering reduces the error rate in detecting genomic variants by short-read sequencing

“…All data from these validation experiments in the tumors (that is, confirmed somatic variants, false-positive and false-negative variants) are accessible in Supplementary Table 1. Functional annotation of SNVs. Several computational tools and databases were used to predict the functional effect of coding and noncoding SNVs, including known or predicted protein coding genes, miRNAs and their target sites 26 , TRANSFAC transcription factor binding sites 44 , OregANNO annotated regulatory sites 45 , Vista Enhancer sites 46 , conservation as indicated by the presence of GERP constraint elements 17 , phastcons conserved elements 47 and repeat elements. The effect of coding mutations was assessed using SIFT 48 , PolyPhen 49 and CanPredict 50 .…”

Gene structures and promoter characteristics of interferon regulatory factor 1 (IRF-1), IRF-2 and IRF-7 from snakehead Channa argus

“…Tertiary structures of CaIRF-1, CaIRF-2 and CaIRF-7 DBD models were predicted by Swiss-model and Swiss-PdbView software (Schwede et al, 2003;Guex and Peitsch, 1997). The sequences of 5 flanking region were analyzed by TRANSFAC software for potential transcriptional factor binding sites (Wingender et al, 2000).…”

Deep sequencing of the mouse lung transcriptome reveals distinct long non-coding RNAs expression associated with the high virulence of H5N1 avian influenza virus in mice

“…Therefore, the bio-functions of this lncRNA were further analyzed using the well-established bioinformatics tools. Transcription factors (TFs) were recognized as important components of signaling cascades controlling all types of normal cellular processes as well as response to external stimulus[47]. Here, TRANSFAC (http://www.gene-regulation.com/index2.html) was used to predict the potential TFs of NONMMUT011061.…”