Domains and Features
Domains Table
Motifs and domains in the Ensembl protein of interest are listed. These are computationally predicted by InterProScan and references listed below. The domains table shows the original project that identified the domain, the amino acid start and end of the domain on the Ensembl peptide, the domain name, and IDs in the original database and InterPro consortium.
Other Features Table
Coiled-coils - The Ensembl analysis and annotation pipeline uses the ncoils program implemented by R.B. Russell and A.N. Lupas for coiled-coil domain characterisation and annotation. Rob Russel's group at the EMBL Heidelberg provides a public service.
- Lupas A, Van Dyke M and Stock J.
Predicting coiled coils from protein sequences.
Science. 1991 May 24;252(5010):1162-1164.
Low-complexity regions - Low complexity regions are annotated with the SEG program.
- Wootton, J. C. and S. Federhen
Statistics of local complexity in amino acid sequences and sequence databases.
Computers in Chemistry 1993; 17:149-163.
- Wootton, J. C. and S. Federhen.
Analysis of compositionally biased regions in sequence databases.
Methods in Enzymology 1996; 266: 554-571.
Signal sequences - These regions are characterised with SignalP.
- Nielsen H, Engelbrecht J, Brunak S, von Heijne G. Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites.
Protein Eng. 1997 Jan;10(1):1-6.
- Nielsen H, Krogh A. Prediction of signal peptides and signal anchors by a hidden Markov model.
In J. Glasgow, T. Littlejohn, F. Major, R. Lathrop, D. Sankoff, and C. Sensen, editors Proceedings of the Sixth International Conference on Intelligent Systems for Molecular Biology, pages 122-130, Menlo Park, CA, 1998.
- Bendtsen JD, Nielsen H, von Heijne G, Brunak S. Improved prediction of signal peptides: SignalP 3.0.
J Mol Biol. 2004 Jul 16;340(4):783-795.
Transmembrane regions - Ensembl uses TMHMM for the annotation of transmebrane helices.
- A. Krogh, B. Larsson, G. von Heijne, and E. L. L. Sonnhammer.
Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes.
Journal of Molecular Biology, 305(3):567-580, January 2001.
- E. L.L. Sonnhammer, G. von Heijne, and A. Krogh.
A hidden Markov model for predicting transmembrane helices in protein sequences. In J. Glasgow, T. Littlejohn, F. Major, R. Lathrop, D. Sankoff, and C. Sensen, editors
Proceedings of the Sixth International Conference on Intelligent Systems for Molecular Biology
175-182, Menlo Park, CA, 1998.