T-REKS: identification of Tandem REpeats in sequences with a K-meanS based algorithm.
BACKGROUND
Over the last years a number of evidences have been accumulated about high incidence of tandem repeats in proteins carrying fundamental biological functions and being related to a number of human diseases. At the same time, frequently, protein repeats are strongly degenerated during evolution and, therefore, cannot be easily identified. To solve this problem, several computer programs which were based on different algorithms have been developed. Nevertheless, our tests showed that there is still room for improvement of methods for accurate and rapid detection of tandem repeats in proteins.


RESULTS
We developed a new program called T-REKS for ab initio identification of the tandem repeats. It is based on clustering of lengths between identical short strings by using a K-means algorithm. Benchmark of the existing programs and T-REKS on several sequence datasets is presented. Our program being linked to the Protein Repeat DataBase opens the way for large-scale analysis of protein tandem repeats. T-REKS can also be applied to the nucleotide sequences.


BACKGROUND
The algorithm has been implemented in JAVA, the program is available upon request at http://bioinfo.montp.cnrs.fr/?r=t-reks. Protein Repeat DataBase generated by using T-REKS is accessible at http://bioinfo.montp.cnrs.fr/?r=repeatDB.
Jorda
Julien
J
Centre de Recherches de Biochimie Macromoléculaire UMR 5237, CNRS, University of Montpellier 1 and 2, Montpellier, France. julien.jorda@crbm.cnrs.fr
Kajava
Andrey V
AV
D000465:Algorithms; D000595:Amino Acid Sequence; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D030562:Databases, Protein; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry; D020449:Repetitive Sequences, Amino Acid; D020539:Sequence Analysis, Protein / Q000379:methods*; D020080:Tandem Repeat Sequences
D011506:Proteins