Genomic Signal Processing 2010
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Citation: EURASIP Journal on Advances in Signal Processing 2011 2010:137263
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A Metastate HMM with Application to Gene Structure Identification in Eukaryotes
We introduce a generalized-clique hidden Markov model (HMM) and apply it to gene finding in eukaryotes (C. elegans). We demonstrate a HMM structure identification platform that is novel and robustly-performing in...
Citation: EURASIP Journal on Advances in Signal Processing 2010 2010:581373 -
Hidden Markov Model with Duration Side Information for Novel HMMD Derivation, with Application to Eukaryotic Gene Finding
We describe a new method to introduce duration into an HMM using side information that can be put in the form of a martingale series. Our method makes use of ratios of duration cumulant probabilities in a mann...
Citation: EURASIP Journal on Advances in Signal Processing 2010 2010:761360 -
Small-Sample Error Estimation for Bagged Classification Rules
Application of ensemble classification rules in genomics and proteomics has become increasingly common. However, the problem of error estimation for these classification rules, particularly for bagging under t...
Citation: EURASIP Journal on Advances in Signal Processing 2010 2010:548906 -
Inferring Parameters of Gene Regulatory Networks via Particle Filtering
Gene regulatory networks are highly complex dynamical systems comprising biomolecular components which interact with each other and through those interactions determine gene expression levels, that is, determi...
Citation: EURASIP Journal on Advances in Signal Processing 2010 2010:204612 -
Novel Data Fusion Method and Exploration of Multiple Information Sources for Transcription Factor Target Gene Prediction
Background. Revealing protein-DNA interactions is a key problem in understanding transcriptional regulation at mechanistic level. Computational methods have an important role in predicting transcription factor ta...
Citation: EURASIP Journal on Advances in Signal Processing 2010 2010:235795 -
An MCMC Algorithm for Target Estimation in Real-Time DNA Microarrays
DNA microarrays detect the presence and quantify the amounts of nucleic acid molecules of interest. They rely on a chemical attraction between the target molecules and their Watson-Crick complements, which ser...
Citation: EURASIP Journal on Advances in Signal Processing 2010 2010:736301 -
Exact Performance of CoD Estimators in Discrete Prediction
The coefficient of determination (CoD) has significant applications in genomics, for example, in the inference of gene regulatory networks. We study several CoD estimators, based upon the resubstitution, leave...
Citation: EURASIP Journal on Advances in Signal Processing 2010 2010:487893 -
Uncovering Transcriptional Regulatory Networks by Sparse Bayesian Factor Model
The problem of uncovering transcriptional regulation by transcription factors (TFs) based on microarray data is considered. A novel Bayesian sparse correlated rectified factor model (BSCRFM) is proposed that m...
Citation: EURASIP Journal on Advances in Signal Processing 2010 2010:538919