Discrete Ramanujan transform for distinguishing the protein coding regions from other regions

Detection of Tandem Repeats in DNA Sequences Using Short-Time Ramanujan Fourier Transform

Tandem repeats in genomic sequences are characterized by two or more contiguous copies of a pattern of nucleotides. The role of these repeats as molecular markers is well established in various genetic disorders, human evolution studies, DNA forensics and intron retention. In this work a computational method has been developed for the extraction of both exact and approximate tandem repeats. The proposed algorithm uses Ramanujan Fourier Transform (RFT) to identify periodicities in the DNA sequences. Since RFT estimates the period directly, rather than inferring it from the signal's spectrum, it provides a more sensitive and rapid detection of tandem repeats as compared to other available popular computational methods.

Hot spots localization in proteins by optimized short time Ramanujan Fourier transform

Specific functions in biological processes are dependent on protein-protein interactions. Hot spot residues play a key role in the determination of these interactions and have wide applications in engineering proteins and drug discovery. Experimental techniques to identify hotspots are often labor intensive and expensive. Also, most of the computational methods which have been developed are structure based and need some training. In this work, hotspots have been identified by sequence information alone using the Resonant Recognition Model (RRM). The proposed method uses characteristic period in place of traditionally used characteristic frequency by RRM-based methods. The characteristic period has been extracted from the consensus spectrum of protein families using the Ramanujan Fourier Transform (RFT). Position-period plots for proteins have been generated using Short Time RFT (ST-RFT) with a Gaussian window. Hot spots have been identified by thresholding of the signal corresponding to the protein's characteristic period in the ST-RFT. To enhance the performance of the ST-RFT, Gaussian window shape parameter has been optimized using concentration measure as a metric. Better sensitivity of this method has been observed compared to other reported RRM-based methods. Since the method is model independent it does not requires any training and can be readily used for any protein sequence provided its interface residues and protein family are known.

Detecting Periodicities in Eukaryotic Genomes by Ramanujan Fourier Transform

Ramanujan Fourier transform (RFT) nowadays is becoming a popular signal processing method. RFT is used to detect periodicities in exons and introns of eukaryotic genomes in this article. Genomic sequences of nine species were analyzed. The highest peak in the spectrum amplitude corresponding to each exon or intron is regarded as the significant signal. Accordingly, the periodicity corresponding to the significant signal can be also regarded as a valuable periodicity. Exons and introns have different periodic phenomena. The computational results reveal that the 2-, 3-, 4-, and 6-base periodicities of exons and introns are four kinds of important periodicities based on RFT. It is the first time that the 2-base periodicity of introns is discovered through signal processing method. The frequencies of the 2-base periodicity and the 3-base periodicity occurrence are polar opposite between the exons and the introns. With regard to the cyclicality of the Ramanujan sums, which is the base function of the transformation, RFT is suggested for studying the periodic features of dinucleotides, trinucleotides, and q nucleotides.