Neural Network in Human Identification by DNA Sequences

Author

Rafeh, Reza ; Mesgar, Mohsen

Author_Institution

Comput. Eng. Dept., Islamic Azad Univ., Malayer, Iran

Volume

2

fYear

2009

fDate

28-30 Dec. 2009

Firstpage

64

Lastpage

67

Abstract

In this paper we propose a new method to analyze the similarity/dissimilarity of DNA sequences which can be used in human identification field. This method is based on the graphical representation proposed by Randic et al [M. Randic, M. Vracko, L. Nella, P. Dejan, Chem. (2003)]. Instead of calculating the leading eigenvalues of the matrix for graphical representation we smooth the zigzag curve and calculate its curvature. Similarity between DNA sequences are decided by neural network. Our method is useful for human identification in criminal investigations and in genetic disease. Our results verify the validity of our method.

Keywords

DNA; biology computing; eigenvalues and eigenfunctions; forensic science; matrix algebra; medical computing; neural nets; DNA sequences; criminal investigations; genetic disease; graphical representation; human identification; matrix eigenvalues; neural network; Artificial neural networks; Computer networks; DNA computing; Diseases; Eigenvalues and eigenfunctions; Forensics; Genetics; Humans; Neural networks; Sequences; Constraint Programming; Linear Programming; Optimization Problems; University Timetabling;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Electrical Engineering, 2009. ICCEE '09. Second International Conference on

Conference_Location

Dubai

Print_ISBN

978-1-4244-5365-8

Electronic_ISBN

978-0-7695-3925-6

Type

conf

DOI

10.1109/ICCEE.2009.132

Filename

5380141