Title :
Genomic analysis using methods from information theory
Author :
Hagenauer, J. ; Dawy, Z. ; Göbel, B. ; Hanus, P. ; Mueller, J.
Author_Institution :
Inst. for Commun. Eng., Munich Univ. of Technol., Munchen, Germany
Abstract :
Methods used in information theory can be used in genomic analysis to provide a more meaningful insight into the genetic process. Using an information transfer model between certain polymorphisms in the human genome (SNP) and certain diseases (e.g. Alzheimer), Shannon´s mutual information can identify the relevant SNP. Several compression algorithms approximating the entropy of DNA sequences are used to distinguish between introns and exons. Certain distance measures derived from DNA sequences allow classification leading to evolutionary trees. They can also be used for content recognition.
Keywords :
DNA; data compression; diseases; entropy; evolution (biological); genetics; pattern classification; sequences; trees (mathematics); Alzheimer disease; DNA sequence entropy; SNP; Shannon mutual information; classification; compression algorithms; content recognition; distance measures; evolutionary trees; exons; genetic process; genomic analysis; human genome; information theory; information transfer model; introns; polymorphisms; Alzheimer´s disease; Bioinformatics; DNA; Genetic communication; Genomics; Humans; Information analysis; Information theory; Mutual information; Sequences;
Conference_Titel :
Information Theory Workshop, 2004. IEEE
Print_ISBN :
0-7803-8720-1
DOI :
10.1109/ITW.2004.1405274
