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Inverted-Repeats-Aware Finite-Context Models for DNA Coding

by O J. Pinho, António J. R. Neves, Paulo J. S. G. Ferreira - In Proceedings of 16th European Signal Processing Conference (EUSIPCO-2008 , 2008
"... Finite-context models have been used for DNA sequence compression as secondary, fall back mechanisms, the gen-eralized opinion being that models with order larger than two or three are inappropriate. In this paper we show that finite-context models can also be used as the main encoding method, and t ..."
Abstract - Cited by 4 (2 self) - Add to MetaCart
Finite-context models have been used for DNA sequence compression as secondary, fall back mechanisms, the gen-eralized opinion being that models with order larger than two or three are inappropriate. In this paper we show that finite-context models can also be used as the main encoding method

DNA Coding using Finite-Context Models and Arithmetic Coding

by O J. Pinho, António J. R. Neves, Carlos A. C. Bastos, Paulo J. S. G. Ferreira - In Proceedings of IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP-2009 , 2009
"... The interest in DNA coding has been growing with the avail-ability 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 algo-rithms ..."
Abstract - Cited by 6 (2 self) - Add to MetaCart
-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 finite-context mod-els have only been used as secondary, fall back mechanisms

Finite-context models for DNA coding 117 0 Finite-context models for DNA coding *

by Armando J Pinho , António J R Neves , Daniel A Martins , Carlos A C Bastos , Paulo J S G Ferreira
"... ..."
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Abstract not found

Context Weighting for General Finite-Context Sources

by Frans M. J. Willems, Yuri M. Shtarkov, Tjalling J. Tjalkens - 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 ..."
Abstract - Cited by 25 (2 self) - Add to MetaCart
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

by David M. Blei, Andrew Y. Ng, Michael I. Jordan, John Lafferty - 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 three-level 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, ..."
Abstract - Cited by 4365 (92 self) - Add to MetaCart
We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level 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 finite-context (Markov) models

by O J. Pinho, Paulo J. S. G. Ferreira, António J. R. Neves, Carlos A. C. Bastos - PLoS ONE , 2011
"... A finite-context (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 ..."
Abstract - Cited by 10 (2 self) - Add to MetaCart
A finite-context (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 THREE-BASE PERIODICITY FOR DNA COMPRESSION AND MODELING

by Paulo J. S. G. Ferreira, António J. R. Neves, Vera Afreixo, O J. Pinho
"... To explore the three-base 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 finite-context model counterpart. Add ..."
Abstract - Cited by 4 (3 self) - Add to MetaCart
To explore the three-base 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 finite-context model counterpart

Constructing Finite-Context Sources From Fractal Representations of Symbolic Sequences

by Peter Tino, Georg Dorffner , 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 n-block structure into a spatial structure of points in a unit hypercube. The transformation between the symbolic and Euclidean spa ..."
Abstract - Cited by 5 (3 self) - Add to MetaCart
We propose a novel approach to constructing predictive models on long complex symbolic sequences. The models are constructed by first transforming the training sequence n-block structure into a spatial structure of points in a unit hypercube. The transformation between the symbolic and Euclidean

L-INFINITY PROGRESSIVE IMAGE COMPRESSION

by unknown authors
"... This paper presents a lossless image coding approach that produces an embedded bit-stream optimized for L∞-constrained decoding. The decoder is implementable using only integer arithmetic and is able to deduce from the bit-stream 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 JPEG-LS and JPEG2000. Operational rate-distortion curves, in the L ∞ sense, are presented and compared with JPEG2000. Index Terms — L-infinity image coding, progressive transmission, finite-context models, binary trees. 1.

PROGRESSIVE LOSSLESS COMPRESSION OF MEDICAL IMAGES

by O J. Pinho, António J. R. Neves
"... This paper describes a lossless compression method for medical im-ages that produces an embedded bit-stream, allowing progressive lossy-to-lossless decoding with L-infinity oriented rate-distortion. The experimental results show that the proposed technique produces better average lossless compressio ..."
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compression results than several other com-pression methods, including JPEG2000, JPEG-LS and JBIG, in a publicly available medical image database containing images from several modalities. Index Terms — Medical image compression, lossless image coding, progressive transmission, finite-context models. 1.
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