Title :
Genomic signal analysis: Study of pathogen variability
Author :
Cristea, Paul Dan
Author_Institution :
Bio-Med. Eng. Center, Politeh. Univ. of Bucharest, Bucharest
Abstract :
The conversion of symbolic nucleotide sequences into digital signals allows applying signal processing methods to analyze genomic data. The method works well for the study of small genomic sequences, such as in the genomes of viruses and bacteria, and is adequate for monitoring their variability and tracking the development of drug resistance. The paper is based on data downloaded from NIH GenBank, and compares the Hemagglutinin (HA) gene in human and avian isolates of the influenza type A, subtype H5N1, virus.
Keywords :
data analysis; diseases; genetics; medical signal processing; microorganisms; sequences; bacteria; digital signal processing; drug resistance; genomic data analysis; genomic sequence; genomic signal analysis; pathogen variability; symbolic nucleotide sequence; virus; Bioinformatics; Data analysis; Digital signal processing; Genomics; Microorganisms; Monitoring; Pathogens; Signal analysis; Signal processing; Viruses (medical);
Conference_Titel :
Genomic Signal Processing and Statistics, 2006. GENSIPS '06. IEEE International Workshop on
Conference_Location :
College Station, TX
Print_ISBN :
1-4244-0384-7
Electronic_ISBN :
1-4244-0385-5
DOI :
10.1109/GENSIPS.2006.353151
