MOTIVATION: Recognition of functional sites remains a key event in the course of genomic DNA annotation. It is well known that a number of sites have their own specific oligonucleotide content. This pinpoints the fact that the preference of the site-specific nucleotide combinations at adjacent positions within an analyzed functional site could be informative for this site recognition. Hence, Web-available resources describing the site-specific oligonucleotide content of the functional DNA sites and applying the above approach for site recognition are needed. However, they have been poorly developed up to now. RESULTS: To describe the specific oligonucleotide content of the functional DNA sites, we introduce the oligonucleotide alphabets, out of which the frequency matrix for a given site could be constructed in addition to a traditional nucleotide frequency matrix. Thus, site recognition accuracy increases. This approach was implemented in the activated MATRIX database accumulating oligonucleotide frequency matrices of the functional DNA sites. We have demonstrated that the false-positive error of the functional site recognition decreases if the oligonucleotide frequency matrixes are added to the nucleotide frequency matrixes commonly used. AVAILABILITY: The MATRIX database is available on the Web, http://wwwmgs.bionet.nsc.ru/Dbases/MATRIX/ and the mirror site, http://www.cbil.upenn.edu/mgs/systems/c onsfreq/.
MOTIVATION: Recognition of functional sites remains a key event in the course of genomic DNA annotation. It is well known that a number of sites have their own specific oligonucleotide content. This pinpoints the fact that the preference of the site-specific nucleotide combinations at adjacent positions within an analyzed functional site could be informative for this site recognition. Hence, Web-available resources describing the site-specific oligonucleotide content of the functional DNA sites and applying the above approach for site recognition are needed. However, they have been poorly developed up to now. RESULTS: To describe the specific oligonucleotide content of the functional DNA sites, we introduce the oligonucleotide alphabets, out of which the frequency matrix for a given site could be constructed in addition to a traditional nucleotide frequency matrix. Thus, site recognition accuracy increases. This approach was implemented in the activated MATRIX database accumulating oligonucleotide frequency matrices of the functional DNA sites. We have demonstrated that the false-positive error of the functional site recognition decreases if the oligonucleotide frequency matrixes are added to the nucleotide frequency matrixes commonly used. AVAILABILITY: The MATRIX database is available on the Web, http://wwwmgs.bionet.nsc.ru/Dbases/MATRIX/ and the mirror site, http://www.cbil.upenn.edu/mgs/systems/c onsfreq/.
Authors: J V Ponomarenko; G V Orlova; M P Ponomarenko; S V Lavryushev; A S Frolov; S V Zybova; N A Kolchanov Journal: Nucleic Acids Res Date: 2000-01-01 Impact factor: 16.971
Authors: J V Ponomarenko; T I Merkulova; G V Vasiliev; Z B Levashova; G V Orlova; S V Lavryushev; O N Fokin; M P Ponomarenko; A S Frolov; A Sarai Journal: Nucleic Acids Res Date: 2001-01-01 Impact factor: 16.971
Authors: Julia V Ponomarenko; Galina V Orlova; Anatoly S Frolov; Mikhail S Gelfand; Mikhail P Ponomarenko Journal: Nucleic Acids Res Date: 2002-01-01 Impact factor: 16.971
Authors: Irina V Chadaeva; Mikhail P Ponomarenko; Dmitry A Rasskazov; Ekaterina B Sharypova; Elena V Kashina; Marina Yu Matveeva; Tatjana V Arshinova; Petr M Ponomarenko; Olga V Arkova; Natalia P Bondar; Ludmila K Savinkova; Nikolay A Kolchanov Journal: BMC Genomics Date: 2016-12-28 Impact factor: 3.969
Authors: Mikhail Ponomarenko; Dmitry Rasskazov; Olga Arkova; Petr Ponomarenko; Valentin Suslov; Ludmila Savinkova; Nikolay Kolchanov Journal: Biomed Res Int Date: 2015-10-04 Impact factor: 3.411
Authors: Victor G Levitsky; Elena V Ignatieva; Elena A Ananko; Igor I Turnaev; Tatyana I Merkulova; Nikolay A Kolchanov; T C Hodgman Journal: BMC Bioinformatics Date: 2007-12-19 Impact factor: 3.169
Authors: Mikhail P Ponomarenko; Olga Arkova; Dmitry Rasskazov; Petr Ponomarenko; Ludmila Savinkova; Nikolay Kolchanov Journal: Front Immunol Date: 2016-04-04 Impact factor: 7.561