Afef Elloumi Oueslati

Spectral Analysis of Global Behaviour of C. Elegans Chromosomes

Afef Elloumi Oueslati1, Imen Messaoudi1, Zied Lachiri2 and Noureddine Ellouze1 Unite Signal, Image et Reconnaissance de Formes, Departement de Genie Electrique, 1Ecole Nationale d’Ingenieurs de Tunis, BP 37, Campus Universitaire, Le Belvedere, 1002, Tunis, 2Departement de Genie Physique et Instrumentation Institut National des Sciences Appliquees et de Technologie, BP 676, Centre Urbain Cedex, 1080, Tunis, Tunisie

Detecting particular features in C. elegans genomes using Synchronous Analysis based on Wavelet Transform

In this paper, synchronous analysis based on wavelet transform is applied to genomic sequences. To focus on the particular feature of periodicity 3 in the protein-coding region of genes, a coding method is applied on the sequence, which will be segmented to form a pitch synchronous representation. This modelling concept captures period of period fluctuation of signals. The wavelet transform enhances the periodicity, and a given threshold is used to make decision about exons positions. The algorithm simulation shows the accuracy of the method in simultaneously locating exons and revealing the reading frame associated.

Wavelet analysis of frequency chaos game signal: a time-frequency signature of the C. elegans DNA

Challenging tasks are encountered in the field of bioinformatics. The choice of the genomic sequence’s mapping technique is one the most fastidious tasks. It shows that a judicious choice would serve in examining periodic patterns distribution that concord with the underlying structure of genomes. Despite that, searching for a coding technique that can highlight all the information contained in the DNA has not yet attracted the attention it deserves. In this paper, we propose a new mapping technique based on the chaos game theory that we call the frequency chaos game signal (FCGS). The particularity of the FCGS coding resides in exploiting the statistical properties of the genomic sequence itself. This may reflect important structural and organizational features of DNA. To prove the usefulness of the FCGS approach in the detection of different local periodic patterns, we use the wavelet analysis because it provides access to information that can be obscured by other time-frequency methods such as the Fourier analysis. Thus, we apply the continuous wavelet transform (CWT) with the complex Morlet wavelet as a mother wavelet function. Scalograms that relate to the organism Caenorhabditis elegans (C. elegans) exhibit a multitude of periodic organization of specific DNA sequences.

Spectral Analysis of DNA Sequence: The Exon's Location Method

The systems analysis concepts based on signal processing methods are considered as very important tools in the genomic fields exploration. Spectral analysis of DNA sequences reveals genomes specific periodicities. Studying one organisms genome requires three steps. First, the DNA coding method: the DNAs string data are transformed into numerical signal. Second periodicities are detected by spectral analysis. Third, following the evolution of this periodicity along the genome allows the exons, or protein coding regions, location. In this paper, we expose the exons location method: including the coding and spectral analysis steps. After, we propose a two dimensional graphical representation for the spectrum. The experimental result including a variety of coding indicators methods reveals the importance of each bases combination, from one base to four group bases, in the exons enhancement. The contributions in percent of each of this groups indicator are finally estimated.

Genomic data visualization

The sequencing of DNA implies an exponentially growing number of genomic data. This mass of information requires excessive work to reveal the location and functions of the characteristic areas in the genomes. In order to make exploratory studies, the alphabets of a DNA sequence need to be mapped onto their corresponding numerical values for visualization and analysis. This paper develops and compares a number of one dimensional and two dimensional mapping approaches. These coding techniques involve the alignment of bases in the polypeptide chains or affect the 3D structure of the DNA molecule.

Nucleosome location method based on morlet wavelet analysis scalograms investigation

In this paper, We propose a method for the nucleosomes location based on the analysis of scalograms generated by morlet wavelet analysis. We compare after these location in genes by focusing on periodicity 3 and 10. For this purpose, we built a nucleosome database. The methodology adopted in building database consists in four steps. First, we obtain the DNA signal with Frequency Chaos Game Signal at order 2 (FCGS2). After applying Wavelet Transform (WT), we generate scalograms images where we have all periodicities. Based on the periodicity 10, new database (scalograms images) of the nucleosome structure is established. Then, we highlight the different patterns associated with these regions and their durations. Finally, we compare the nucleosome positions with genes region.

Tandem repeat search tools performance for the Arabidopsis thaliana genome

In eukaryotic genomes, tandem repeats represent two or more adjacent copies of pattern nucleotides. They are the most principal cause of various genetic diseases. So, its very important to locate and define them. During the last decade, many tools (TRF (Tandem Repeats Finder), Mreps, Sputnik, ATRHunter equicktandem, etandem...) have been developed to search tandem repeats in DNA sequences. However, search algorithm results are various. It is not easy to choose appropriate parameters settings for each one. In addition, when varying the parameter settings for a particular tool, the user can found different results. In this paper, we present uses of four tools for search tandem repeats and we investigate Arabidopsis thalianas sequence to compare the softwares performance.

ECG image representation of normal sinus rythm

This paper deals with a new image representation for ECG signal. The method consists in decomposing the ECG signal in beats. The ECG segmentation is based on the time location of the peak R of the QRS complex. A matrix parameterized by QRS rank comprises the signal tranches around this time reference. The matrix forms an image that illustrates the ECG signal characteristics to replace the long ECG record signal. This representation is very useful for diagnosis in both normal and heart diseases cases. The different ECG records are given from the Arrhythmias database. In this work, we focus on the normal sinus rhythm to show the performances of this representation.

A combined support vector machine-FCGS classification based on the wavelet transform for Helitrons recognition in C.elegans

The Helitrons, an important sub-class of the transposable elements (TEs) class II, have been revealed in diverse eukaryotic genomes. They are mobile elements with great impact on genomic evolution. Till today, there is no systematic classification model of helitrons; that’s why we thought of creating an efficient automatic model to identify these sequences. This paper focuses on the discrimination between helitrons and non-helitrons using the Support Vector Machine (SVM). In this study, we use all the SVM kernels and the higher accuracy rates are obtained by reaching the optimal kernels-parameters (d, c and σ). Further, we introduce two methods to represent the genomic sequences in the form of features to be considered later for the classification task: (i) the temporal and the spectral features extracted from the Frequency Chaos Game Signals order 2 (FCGS2) (ii) the features extracted from the Continuous Wavelet Transform (CWT) applied to the FCGS2 signals. The dataset we used regards two types DNA classes in C.elegans: the helitrons and the repetitive DNA sequences that contain microsatellites and do not form helitrons. The classification results prove that the wavelet energy feature is more effective than the FCGS2 features in the helitron’s recognition system. The performance of our system achieves a high recognition rate (Globally accuracy rate) reaching the value of 92.27%.

A Novel methodology for Helitron's classification by SVM based on time frequency representation

Helitron is considered as very important type of DNA involved in mechanisms evolution. These elements are not well studied and the major researches done are biological experiments. In this paper, we propose a novel approach aiming to characterize and classify helitrons types. Accordingly, we use the Support Vector Machine (SVM) classification technique known to be preferment in DNA related studies. We opt for the RBF kernel function after testing different kernel. Furthermore, we used the Wavelet coefficients features. These features are the direct result of the Complex Morlet Wavelet Transform applied to binary input form of DNA sequence resulting from the new FCGS coding technique.