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Volumn 2003-January, Issue , 2003, Pages 253-262

DNA sequence compression using the normalized maximum likelihood model for discrete regression

Author keywords

Biological information theory; Biological system modeling; Biomedical signal processing; Data compression; Dictionaries; DNA; Encoding; Entropy; History; Sequences

Indexed keywords

BIOLOGICAL SYSTEMS; BIOMEDICAL SIGNAL PROCESSING; DATA HANDLING; DNA; DNA SEQUENCES; ENCODING (SYMBOLS); ENTROPY; GLOSSARIES; HISTORY; INFORMATION THEORY; MARKOV PROCESSES; MAXIMUM LIKELIHOOD; RANGE FINDING; SIGNAL PROCESSING;

EID: 34547630306     PISSN: 10680314     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DCC.2003.1194016     Document Type: Conference Paper
Times cited : (54)

References (14)
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  • 3
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  • 5
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    • July/August
    • X. Chen, S. Kwong, M. Li A compression algorithm for DNA sequences: using approximate matching for better compression ratio to reveal the true characteristics of DNA, IEEE Engineering in Medicine and Biology, vol.20:4, pp. 61-66, July/August 2001.
    • (2001) IEEE Engineering in Medicine and Biology , vol.20 , Issue.4 , pp. 61-66
    • Chen, X.1    Kwong, S.2    Li, M.3
  • 6
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  • 11
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    • Strong optimality of the normalized ML models as universal codes and information in data
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  • 14
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    • Classification and feature gene selection using the normalized maximum likelihood model for discrete regression
    • in print
    • I. Tabus, J. Rissanen, J. Astola, Classification and feature gene selection using the normalized maximum likelihood model for discrete regression. Signal Processing, Special issue on genomic signal processing, in print. Also available at http://sigwww.cs.tut.fi/-tabus/GSP.pdf
    • Signal Processing, Special Issue on Genomic Signal Processing
    • Tabus, I.1    Rissanen, J.2    Astola, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.