DocumentCode :
1991285
Title :
Normalized maximum likelihood models for genomics
Author :
Tabus, Ioan ; Rissanen, Jorma ; Astola, Jaakko
Author_Institution :
Inst. of Signal Process., Tampere Univ. of Technol., Tampere
fYear :
2007
fDate :
12-15 Feb. 2007
Firstpage :
1
Lastpage :
6
Abstract :
We present NML models for discrete models and show how to apply the minimum description principle to them to obtain structure information. Then we summarize methods derived in our previous works, and we treat in a unified manner all the usual discrete models. In the last part we describe important applications of the proposed models to disease classification.
Keywords :
diseases; genetics; matrix algebra; maximum likelihood estimation; medical computing; pattern classification; NML models; discrete models; disease classification; genomics; matrix algebra; minimum description principle; normalized maximum likelihood models; structure information; Bioinformatics; Biological information theory; Biological system modeling; Data mining; Diseases; Gene expression; Genomics; Signal processing; Testing; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on
Conference_Location :
Sharjah
Print_ISBN :
978-1-4244-0778-1
Electronic_ISBN :
978-1-4244-1779-8
Type :
conf
DOI :
10.1109/ISSPA.2007.4555629
Filename :
4555629
Link To Document :
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