Transcription factor binding site recognition by regularity matrices based on the natural classification method

Issue title: New Methods in Bioinformatics Presented at the Fifth International Conference on Bioinformatics of Genome Regulation and Structure

Guest editors: Evgenii Vityaevx and Nikolay Kolchanovy

Article type: Research Article

Authors: Vityaev, E.E.^{a; b; *} | Lapardin, K.A.^b | Khomicheva, I.V.^c | Proskura, A.L.^c

Affiliations: [a] Institute of Mathematics SB RAS, Novosibirsk, Russia | [b] Novosibirsk State University, Novosibirsk, Russia | [c] Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia | [x] Sobolev Institute of Mathematics, Koptyug aven. 4, Novosibirsk, 630090, Russia | [y] Laboratory of Theoretical Genetics, Institute of Cytology and Genetics, Novosibirsk, 630090, Russia

Correspondence: [*] Corresponding author. Fax: +7 383 333 25 98; E-mail: vityaev@bionet.nsc.ru

Abstract: A principally new approach to the classifications of nucleotide sequences based on the “natural” classification concept is proposed. As a result of “natural” classification of the nucleotide sequences, we obtain regularity matrices, where nucleotides are interconnected by regularities. Method, algorithm and software system DNANatClass for performing the “natural” classification have been developed. Experimental results comparing weight matrices with regularity matrices are presented. In this experiment, site recognition by regularity matrices appears to be more accurate than by weight matrixes.

DOI: 10.3233/IDA-2008-12505

Journal: Intelligent Data Analysis, vol. 12, no. 5, pp. 495-512, 2008