TY  - GEN
N1  - The universal seven-cluster structure of genetic texts is presented. This structure seems to be important, simple and geometrically elegant, as one can see from the illustrations. It could be interesting for the experts in genomics as well as for the scientists from other fields.


ID  - cogprints3077
UR  - http://cogprints.org/3077/
A1  - Gorban, Prof. Alexander N.
A1  - Zinovyev, Dr. Andrei Yu
A1  - Popova, Dr. Tatyana G.
TI  - Seven clusters in genomic triplet distributions
Y1  - 2002///
N2  -    Motivation: In several recent papers new algorithms were proposed for detecting coding regions without requiring learning dataset of already known genes. In this paper we studied cluster structure of several genomes in the space of codon usage. This allowed to interpret some of the results obtained in other studies and propose a simpler method, which is, nevertheless, fully
functional.  
   Results: Several complete genomic sequences were analyzed, using visualization of tables of triplet counts in a sliding window. The distribution of 64-dimensional vectors of triplet frequencies displays a well-detectable cluster structure. The structure was found to consist of seven clusters, corresponding to protein-coding information in three possible phases in one of the two complementary strands and in the non-coding regions. Awareness of the existence of this structure allows development of methods for the segmentation of sequences into regions with the same coding phase and non-coding regions.
   This method may be completely unsupervised or use some external information. Since the method does not need extraction of ORFs, it can be applied even for unassembled genomes. Accuracy calculated on the base-pair level (both sensitivity and specificity) exceeds 90%. This is not worse as compared to such methods as HMM, however, has the advantage to be much simpler and clear.

AV  - public
KW  - genomic
KW  -  cluster
KW  -  gene finding
KW  -  data vizualization
KW  -  codon usage
ER  -

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