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InvertedRepeatsAware FiniteContext Models for DNA Coding
 In Proceedings of 16th European Signal Processing Conference (EUSIPCO2008
, 2008
"... Finitecontext models have been used for DNA sequence compression as secondary, fall back mechanisms, the generalized opinion being that models with order larger than two or three are inappropriate. In this paper we show that finitecontext models can also be used as the main encoding method, and t ..."
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Cited by 4 (2 self)
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Finitecontext models have been used for DNA sequence compression as secondary, fall back mechanisms, the generalized opinion being that models with order larger than two or three are inappropriate. In this paper we show that finitecontext models can also be used as the main encoding method
DNA Coding using FiniteContext Models and Arithmetic Coding
 In Proceedings of IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP2009
, 2009
"... The interest in DNA coding has been growing with the availability of extensive genomic databases. Although only two bits are sufficient to encode the four DNA bases, efficient lossless compression methods are still needed due to the size of DNA sequences and because standard compression algorithms ..."
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Cited by 6 (2 self)
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rithms do not perform well on DNA sequences. As a result, several specific coding methods have been proposed. Most of these methods are based on searching procedures for finding exact or approximate repeats. Low order finitecontext models have only been used as secondary, fall back mechanisms
Context Weighting for General FiniteContext Sources
 IEEE Trans. Inform. Theory
, 1996
"... Context weighting procedures are presented for sources with models (structures) in four different classes. Although the procedures are designed for universal data compression purposes, their generality allows application in the area of classification. 1 Introduction Recently in [14],[15] the author ..."
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Cited by 25 (2 self)
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Context weighting procedures are presented for sources with models (structures) in four different classes. Although the procedures are designed for universal data compression purposes, their generality allows application in the area of classification. 1 Introduction Recently in [14
Latent dirichlet allocation
 Journal of Machine Learning Research
, 2003
"... We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a threelevel hierarchical Bayesian model, in which each item of a collection is modeled as a finite mixture over an underlying set of topics. Each topic is, ..."
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Cited by 4365 (92 self)
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We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a threelevel hierarchical Bayesian model, in which each item of a collection is modeled as a finite mixture over an underlying set of topics. Each topic is
On the representability of complete genomes by multiple competing finitecontext (Markov) models
 PLoS ONE
, 2011
"... A finitecontext (Markov) model of order k yields the probability distribution of the next symbol in a sequence of symbols, given the recent past up to depth k. Markov modeling has long been applied to DNA sequences, for example to find genecoding regions. With the first studies came the discovery t ..."
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Cited by 10 (2 self)
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A finitecontext (Markov) model of order k yields the probability distribution of the next symbol in a sequence of symbols, given the recent past up to depth k. Markov modeling has long been applied to DNA sequences, for example to find genecoding regions. With the first studies came the discovery
EXPLORING THREEBASE PERIODICITY FOR DNA COMPRESSION AND MODELING
"... To explore the threebase periodicity often found in proteincoding DNA regions, we introduce a DNA model based on three deterministic states, where each state implements a finitecontext model. The results obtained show compression gains in relation to the single finitecontext model counterpart. Add ..."
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Cited by 4 (3 self)
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To explore the threebase periodicity often found in proteincoding DNA regions, we introduce a DNA model based on three deterministic states, where each state implements a finitecontext model. The results obtained show compression gains in relation to the single finitecontext model counterpart
Constructing FiniteContext Sources From Fractal Representations of Symbolic Sequences
, 1998
"... We propose a novel approach to constructing predictive models on long complex symbolic sequences. The models are constructed by first transforming the training sequence nblock structure into a spatial structure of points in a unit hypercube. The transformation between the symbolic and Euclidean spa ..."
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Cited by 5 (3 self)
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We propose a novel approach to constructing predictive models on long complex symbolic sequences. The models are constructed by first transforming the training sequence nblock structure into a spatial structure of points in a unit hypercube. The transformation between the symbolic and Euclidean
LINFINITY PROGRESSIVE IMAGE COMPRESSION
"... This paper presents a lossless image coding approach that produces an embedded bitstream optimized for L∞constrained decoding. The decoder is implementable using only integer arithmetic and is able to deduce from the bitstream the L ∞ error that affects the reconstructed image at an arbitrary poi ..."
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point of decoding. The lossless coding performance is compared with JPEGLS and JPEG2000. Operational ratedistortion curves, in the L ∞ sense, are presented and compared with JPEG2000. Index Terms — Linfinity image coding, progressive transmission, finitecontext models, binary trees. 1.
PROGRESSIVE LOSSLESS COMPRESSION OF MEDICAL IMAGES
"... This paper describes a lossless compression method for medical images that produces an embedded bitstream, allowing progressive lossytolossless decoding with Linfinity oriented ratedistortion. The experimental results show that the proposed technique produces better average lossless compressio ..."
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compression results than several other compression methods, including JPEG2000, JPEGLS and JBIG, in a publicly available medical image database containing images from several modalities. Index Terms — Medical image compression, lossless image coding, progressive transmission, finitecontext models. 1.
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