Thursday 25th of April 2024
 

Unsupervised classification of Eukaryotic DNA sequences using Multi Library Wavelet Networks


Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar and Houssine Tlig

The comparative genomics is the comparative study of the structure and function of genomes of different species. It allows to identifying, classifying and understanding the effects of selection on the organization and evolution of genomes. This new research benefits from the increasing number of sequenced genomes. Genomic sequences allow to classify organisms into different categories and classes which have significant biological knowledge and can justify the evolution and identification of unknown organisms. Our system consists in three phases. The first phase is called transformation which is composed of three steps; binary codification of DNA sequence, Fourier Transform and Power Spectrum Signal Processing. The second phase is called approximation. This phase is empowered by the use of Multi Library Wavelet Neural Networks (MLWNN).The third phase is called classification which is realized by applying the algorithm of hierarchical classification. The results of this contribution are more interesting in comparison with some others works, in terms of rate classification using Eukaryotic organisms database. This method permits to avoid the complexity problem of form and structure in different classes of organisms.

Keywords: Classification, DNA sequence, Beta wavelet networks, Power Spectrum, Fourier Transform, Multi Library Wavelet Neural Networks.

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ABOUT THE AUTHORS

Abdesselem Dakhli
Abdesselem dakhli continued these academic studies to FSEG Sfax ,Tunisia. He obtained his teacher’s cerificate in data processing applied to management in June 2001. He continued his degree of Masters in ISIMG of Gabes, Tunisia in 2008. In 2010, he received his Master degree in Information system in the same Institute. In August 2005 he was assigned to the ISG Gabes, Tunisia. Currently, he is a teacher at ISG. In 2012, now he prepares a Phd thesis of bioinformatic in ENIS. Abdesselem dakhli he also participated in one internationnale conference. His areas of research are: Tomography, Bioinformatics.

Wajdi Bellil
Wajdi BELLIL received the B.S. degree in Electrical Engineering from the National Engineering School of Sfax (ENIS) in 2000, the M.S. and PhD degrees in Electrical Engineering from the National Engineering School of Sfax (ENIS), in 2003 and 2009, respectively. He spent five years at the ISET Gafsa, Tunisia, as a technologic assistant and researcher before joining the faculty of Science of Gafsa, Tunisia, as Assistant. He joined the Higher Institute of Applied Sciences and Technology, Gafsa University, where he is currently an assistant professor in the Department of computer science. He was a member of the REsearch Group on Intelligent Machines (REGIM). He is a junior member of IEEE.

Chokri Ben Amar
Chokri BEN AMAR received the B.S. degree in Electrical Engineering from the National Engineering School of Sfax (ENIS) in 1989, the M.S. and PhD degrees in Computer Engineering from the National Institute of Applied Sciences in Lyon, France, in 1990 and 1994, respectively. He spent one year at the University of "Haute Savoie" (France) as a teaching assistant and researcher before joining the higher School of Sciences and Techniques of Tunis as Assistant Professor in 1995. In 1999, he joined the Sfax University (USS), where he is currently a professor in the Department of Electrical Engineering of the National Engineering School of Sfax (ENIS), He is a senior member of IEEE, and the chair of the IEEE SPS Tunisia Chapter since 2009. He was the chair of the IEEE NGNS’2011 (IEEE Third International Conference on Next Generation Networks and Services) and the Workshop on Intelligent Machines.

Houssine Tlig
Houssine TLIG Received his Ph.D. (Quantitative Methods) degree in 2012 from university of Sfax , Tunisia. He is presently working as Assistant in the National Engineering School of Gabes, Tunisia. His research interest includes Optimization, Fuzzy Sets, Stochastic Systems and Data minin


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