TRANSFAC® release 2021.1
The TRANSFAC® database on transcription factors, their genomic binding sites and DNA-binding motifs (PWMs), contains these new data features:
- Integration of new human ChIP-Seq experiments from ENCODE
415 new human transcription factor binding site ChIP-Seq experiments released by the ENCODE phase 4 project between June 2020 and September 2020 have been integrated. The data sets comprise 4,768,755 fragments bound by 391 distinct transcription factors, of which 214 factors were not yet covered by ChIP-Seq data in TRANSFAC.
For 336 of the sets, an existing positional weight matrix for the respective transcription factor was used together with the MATCH tool to predict altogether 3,652,932 best binding sites inside the fragments.
Predicted best binding sites as well as complete fragments are available in FASTA and BED format via the ChIP Experiment Reports, as are lists of genes in a distance range to the fragments as specified by the user.
- New matrices derived from ENCODE ChIP-Seq data
128 new positional weight matrices have been generated from new ENCODE phase 4 ChIP-Seq data and integrated into the TRANSFAC matrix library.
- JASPAR 2020 matrix library integration
New position frequency matrices from the JASPAR 2020 release either added as matrix entries (200 cases) or hyperlinked to existing counterparts in the TRANSFAC matrix library.
Genomic information for genes, promoters, and ChIP fragments for the species human, mouse, rat, pig, macaque, Drosophila, and Arabidopsis is now based on Ensembl release 101.
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Learn more about promoter analysis with TRANSFAC® in the geneXplain platform.
Most transcription factors (TFs) possess a DNA-binding domain (DBD), which mediates the recognition of specific, short DNA sequence elements in promoter, enhancer, etc. In order to approach the problem of deciphering the underlying DNA-protein recognition code, we have completely revised an earlier TF classification scheme (1,2) by adapting it to the wealth of data that were reported during the last ten years (TFClass; 3-5). TFClass has been implemented at the Dept. of Bioinformatics at the University Medical Center Göttingen (3,6).
Part of this work was done in the context of the Syscol
project, where our partner at the Karolinska institute (Prof. J. Taipale and his team) have characterized the DNA-binding profiles of more than 400 mammalian TFs (7). It will be tempting to compare the similarities of their matrices with the DBD classification reported here, and with our own approaches to classify DNA-binding profiles (8).
- Wingender, E., Schoeps, T., Haubrock, M., Krull, M. and Dönitz, J. (2018) TFClass: expanding the classification of human transcription factors to their mammalian orthologs. Nucleic Acids Res. 46, D343-D347. Link
- Wingender, E., Schoeps, T., Haubrock, M., Dönitz, J. (2015) TFClass: a classification of human transcription factors and their rodent orthologs. Nucleic Acids Res. 43, D97-D102. Link
- Stegmaier, P., Kel, A., Wingender, E., Borlak, J. (2013) A discriminative approach for unsupervised clustering of DNA sequence motifs. PLoS Comput. Biol. 9, e1002958.
- Jolma, A., et al. (2013) DNA-Binding Specificities of Human Transcription Factors. Cell, 152, 327–339. Link
- Wingender, E. (2013) Criteria for an updated classification of human transcription factor DNA-binding domains. J. Bioinform. Comput. Biol. 11, in press. Link
- Wingender, E., Schoeps, T., Dönitz, J. (2013) TFClass: An expandable hierarchical classification of human transcription factors. Nucleic Acids Res. 41, D165-D170. Link
- Heinemeyer, T., Chen, X., Karas, H., Kel, A.E., Kel, O.V., Liebich, I., Meinhardt, T., Reuter, I., Schacherer, F., Wingender,E. (1999) Expanding the TRANSFAC database towards an expert system of regulatory molecular mechanisms. Nucleic Acids Res., 27, 318–322. Link
- Wingender, E. (1997) Classification scheme of eukaryotic transcription factors. Mol. Biol. Engl. Tr. 31, 498-512. Link
Wingender, E., Schoeps, T., Haubrock, M., Krull, M. and Dönitz, J. (2018) TFClass: expanding the classification of human transcription factors to their mammalian orthologs. Nucleic Acids Res. 46, D343-D347. PubMed.
Kaplun, A., Krull, M., Lakshman, K., Matys, V., Lewicki, B., Hogan, J.D. (2016) Establishing and validating regulatory regions for variant annotation and expression analysis. BMC Genomics 17 (Suppl. 2):393. PubMed.
Wingender, E. (2008) The TRANSFAC project as an example of framework technology that supports the analysis of genomic regulation. Brief. Bioinform. 9:326-332. PubMed.
Matys, V., Kel-Margoulis, O.V., Fricke, E., Liebich, I., Land, S., Barre-Dirrie, A., Reuter, I., Chekmenev, D., Krull, M., Hornischer, K., Voss, N., Stegmaier, P., Lewicki-Potapov, B., Saxel, H., Kel, A.E., Wingender, E. (2006) TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes. Nucleic Acids Res. 34:D108-D110. PubMed.
Kel, A.E., Gössling, E., Reuter, I., Cheremushkin, E., Kel-Margoulis, O.V., Wingender, E. (2003) MATCH: A tool for searching transcription factor binding sites in DNA sequences. Nucleic Acids Res. 31:3576-3579. PubMed
Wingender, E., Dietze, P., Karas, H., Knüppel, R. (1996) TRANSFAC: a database on transcription factors and their DNA binding sites. Nucleic Acids Res. 24:238-241. PubMed
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