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TFClass


NAR Molecular Biology Database Collection entry number 1571
Edgar Wingender1,2, Torsten Schoeps1 and Jürgen Dönitz1
1. Department of Bioinformatics, University Medical Center Göttingen, Georg August University, D-37077 Göttingen, Germany 2. geneXplain GmbH, D-38302 Wolfenbüttel, Germany

Database Description

TFClass (http://tfclass.bioinf.med.uni-goettingen.de/) provides a comprehensive classification of human transcription factors (TFs), based on their DNA-binding domains. Transcription factors constitute a large functional family of proteins directly regulating the activity of genes. Most of them are sequence-specific DNA-binding proteins, thus reading out the information encoded in cis-regulatory DNA elements of promoters, enhancers and other regulatory regions of a genome. TFClass updates earlier attempts to classify eukaryotic transcription factors (1, 2); it is a database that classifies (so far) human transcription factors by a six-level classification schema, four of which are abstractions according to different criteria, while the fifth level represents TF genes and the sixth individual gene products. With this classification, we hope to provide a basis for deciphering protein-DNA recognition codes; moreover, it can be used for constructing expanded transcriptional networks by inferring additional TF-target gene relations.

Recent Developments

Altogether, 9 superclasses have been identified so far, comprising 40 classes, and 111 families. Counted by genes, 1558 human TFs have been classified so far, or more than 2904 different TFs when including their isoforms that are generated by alternative splicing or protein processing events. Additional specific information is provided for each entry, such as descriptive definitions for superclasses and classes, alignments and logo plots for classes, typical DNA-binding sites for families and subfamilies, and database links to UniProt (3), TRANSFAC (4), Protein Atlas (5) and BioGPS (6) for TF genes and proteins. Making use of data from the Protein Atlas, expression patterns are tabulated according to tissues and cell types, linked to the Cytomer ontology of anatomical entities (7). Exploiting the capabilities of our recently published ontology server OBA, Ontology Based Answers (8), the classification has been implemented as an ontology and is available in obo format for download.

Acknowledgements

This work has been partially funded under the EU FP7 programme (contract numbers 202272, LipidomicNet, and 258236, SysCol). In addition, we acknowledge the financial support by a grant from the German Ministry of Education and Research (BMBF grant no. FKZ0315890B, GerontoShield). The authors wish to thank Olga Kel-Margoulis (geneXplain GmbH) for her constant advice, and Volker Matys and Mathias Krull (BIOBASE GmbH) for their help in providing the links to the TRANSFAC database.

References

1. Wingender,E. (1997) Classification of eukaryotic transcription factors. Mol. Biol. Engl. Tr., 31, 483-497.

2. Heinemeyer,T., Chen,X., Karas,H., Kel,A.E., Kel,O.V., Liebich,I., Meinhardt,T., Reuter,I., Schacherer,F. and Wingender,E. (1999) Expanding the TRANSFAC database towards an expert system of regulatory molecular mechanisms. Nucleic Acids Res., 27, 318-322.

3. UniProt Consortium (2012) Reorganizing the protein space at the Universal Protein Resource (UniProt). Nucleic Acids Res., 40, D71-D75.

4. Wingender,E. (2008) The TRANSFAC project as an example of framework technology that supports the analysis of genomic regulation. Brief. Bioinform., 9, 326-332.

5. Uhlen,M., Oksvold,P., Fagerberg,L., Lundberg,E., Jonasson,K., Forsberg,M., Zwahlen,M., Kampf,C., Wester,K., Hober,S., Wernerus,H., Björling,L. and Ponten,F. (2010) Towards a knowledge-based Human Protein Atlas. Nat. Biotechnol., 28,1248-1250.

6. Wu,C., Orozco,C., Boyer,J., Leglise,M., Goodale,J., Batalov,S., Hodge,C.L., Haase,J., Janes,J., Huss,J.W.3rd and Su,A.I. (2009) BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources. Genome Biol., 10, R130.

7. Dönitz,J., Goemann,B., Lizé,M., Michael,H., Sasse,N., Wingender,E. and Potapov,A.P. (2008) EndoNet: an information resource about regulatory networks of cell-to-cell communication. Nucleic Acids Res., 36, D689-D694.

8. Dönitz,J. and Wingender,E. (2012) The ontology-based answers (OBA) service: A connector for embedded usage of ontologies in applications. Front. Gene., 3, 197.



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