Paper Info
Title
Normalized maximum likelihood model of order-1 for the compression of DNA sequences
Abstract
We present the NML model for classes of models with memory described by first order dependencies. The model is used for efficiently locating and encoding the best regressor present in a dictionary. By combining the order-1 NML with the order- 0 NML model the resulting algorithm achieves a consistent improvement over the earlier order-0 NML algorithm, and it is demonstrated to have superior performance on the practical compression of the human genome.
Year
DOI
Venue
2007
10.1109/DCC.2007.60
DCC
Keywords
Field
DocType
order-0 nml algorithm,consistent improvement,dna sequence,normalized maximum likelihood model,human genome,order dependency,practical compression,resulting algorithm,nml model,regressor present,order-1 nml,superior performance,bioinformatics,genomics,data compression,pattern matching,first order,context modeling,compression algorithms,dictionaries,dna,sequences,maximum likelihood estimation
Compression (physics),Pattern recognition,First order,Computer science,Context model,Normalized maximum likelihood,Artificial intelligence,DNA sequencing,Data compression,Pattern matching,Encoding (memory)
Conference
ISSN
ISBN
Citations 
1068-0314
0-7695-2791-4
7
PageRank 
References 
Authors
0.62
8
2
Name
Order
Citations
PageRank
Gergely Korodi1785.57
Ioan Tabus227638.23