Comparative analysis of periodicity search methods in DNA sequences

BioMed Research International

2017

Self Cite

Summary. We analyzed several prokaryotic and eukaryotic genomes looking for the periodicity sequences availability and employing a new mathematical method. The method envisaged using the random position weight matrices and dynamic programming. Insertions and deletions were allowed inside periodicities, thus adding a novelty to the results we obtained. A periodicity length, one of the key periodicity features, varied from 2 to 50 nt. Totally over 60,000 periodicity sequences were found in 15 genomes including some chromosomes of the H. sapiens (partial), C. elegans, D. melanogaster, and A. thaliana genomes.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Database of Periodic DNA Regions in Major Genomes

Frenkel

Korotkova

BioMed Research International

2017

Self Cite

“…A periodicity is considered as latent if the similarity between any two periods is not statistically significant or if it belongs to the twilight zone (Durbin et al, 1998). Perfect periodicity can become latent periodicity if it accumulates over 1.0 mutations per amino acid in the studied sequence (Suvorova et al, 2014). The distinctive property of latent periodicity is that it cannot be detected by pairwise comparisons of amino acid sequences (Turutina et al, 2006).…”

Section: Inтroductionmentioning

confidence: 99%

“…Spectral approaches enable the discovery of enough "fuzzy" periodicity in protein sequences without insertion(s) or deletion(s) of amino acids. Fourier transform, wavelet transform, information decomposition and some other methods can be attributed to a number of spectral methods (Tiwari et al, 1997;Lobzin and Chechetkin, 2000;Kravatskaya et al, 2011;Korotkov et al, 2003a;de Sousa Vieira, 1999;Meng et al, 2013;Suvorova et al, 2014;Sosa et al, 2013;Kumar et al, 2006). However, these approaches have a significant limitation, such as the fact that they do not allow the detection of periodicity with insertions and deletions.…”

Section: Inтroductionmentioning

confidence: 99%

Search for Latent Periodicity in Amino Acid Sequences with Insertions and Deletions

Pugacheva

Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies

2016

The aim of this study was to show that amino acid sequences have a latent periodicity with insertions and deletions of amino acids in unknown positions of the analyzed sequence. Genetic algorithm, dynamic programming, and random weight matrices were used to develop the new mathematical algorithm for latent periodicity search. The method makes the direct optimization of the position-weight matrix for multiple sequence alignment without using pairwise alignments. The developed algorithm was applied to analyze the amino acid sequences of a small number of proteins. This study showed the presence of latent periodicity with insertions and deletions in the amino acid sequences of such proteins, for which the presence of latent periodicity was not previously known. The origin of latent periodicity with insertions and deletions is discussed.

“…It cannot be done with the help of all known mathematical methods. Previous studies have searched for insertions or deletions (Rastogi et al, 2006), but failed to find a periodicity with large noise (Suvorova et al, 2014). It is right mainly for dynamic programming.…”

mentioning

confidence: 99%

Study of the periodicity in Euro-US Dollar exchange rates using local alignment and random matrices

Korotkova

2017

The purpose of this study was to detect latent periodicity in the presence of deletions or insertions in the analyzed data, when the points of deletions or insertions are unknown. A mathematical method was developed to search for periodicity in the numerical series, using dynamic programming and random matrices. The developed method was applied to search for periodicity in the Euro/Dollar (Eu/$) exchange rate. The presence of periodicity within the period length equal to 24 hours and 25 hours, in the analyzed financial series, was shown. Periodicity can be detected only with insertions and deletions. The results of this study show that periodicity phase shifts, depend on the observation time. A period of 24 hours is a common phenomenon for foreign exchange rates, indices and stocks of different companies. We show it for the Bank of America and Microsoft stocks, S&P500 and NASDAG indexes and for the gold and silver prices as examples. The reasons for the existence of the periodicity in the financial ranks are discussed. The results can find application in computer systems, for the purpose of forecasting exchange rates.