Walsh code based numerical mapping method for the identification of protein coding regions in eukaryotes Abstract   The protein coding regions play a significant role for gene applications in genomic signal processing. Unlike prokaryotes, the coding regions in eukaryotes are arranged in a random manner. Owing to unequal lengths and low volume density of coding regions, the identification of coding regions makes cumbersome. In this work, a new numerical mapping method based on Walsh codes is proposed to detect the coding regions in eukaryotes. The Walsh code for each nucleotide is obtained using the statistical features of a DNA sequence. The proposed method uses static type of mapping to convert a string of DNA nucleotides into a numerical sequence. The numerical sequence is given as an input to the digital signal processing based spectrum identification tool to detect the existence of quasiperiodic components within the coding region. The advantage of our method is that it is simple to design and easy to represent. The performance of the proposed method has been tested on four benchmark databases and a random set of sequences collected from the National Center for Biological Information (NCBI) database. Furthermore, it has been compared with other stateoftheart spectrum based numerical mapping methods for statistical features such as sensitivity, specificity and accuracy. The proposed method is efficient as it attains 94 % accuracy, 85 % sensitivity and 96 % specificity when tested on the benchmark C. Elegans gene sequence.

Low Complexity Frequency Monitoring Filter for Fast Exon Prediction Sequence Analysis Over the last few years, the application of Digital Signal Processing (DSP) techniques for genomic sequence analysis has received great interest. Indeed, among its applications in genomic analysis, it has been demonstrated that DSP can be used to detect protein coding regions (exons) among noncoding regions in a DNA sequence. The period3 behavior exhibited by exons is one of its features that has been exploited in several developed algorithms for exon prediction. Identification of this periodicity in genomic sequences can be done by using different methods such as the wellknown Fast Fourier Transform (FFT) and the Goertzel algorithm for complexity reduction in which the reduction of computational time is a great challenge in genomic analysis. Therefore, this paper presents a novel one frequency analysis by using half of the arithmetic complexity of the Goertzel algorithm for gene prediction. Compared to the Intelxc2xaexe2x80x99s FFT (MKL) optimized function, the Goertzelxe2x80x99s (IPP) and the dedicated Goertzel compiled function with ICC on Xeon CPU (24 cores), the proposed method conserves the same accuracy provided by the referenced methods which will manifest a speedup of 3000, 10 and 2 compared to MKL FFT, IPP Goertzel and the dedicated Goertzel with ICC, respectively.