Bayesian hierarchicalmodel for estimating gene expression intensity using multiple scanned microarrays
We propose a method for improving the quality of signal from DNA microarrays by using several scans at varying scanner sensitivities. A Bayesian latent intensity model is introduced for the analysis of such data. The method improves the accuracy at ...
A time-series-based feature extraction approach for prediction of protein structural class
This paper presents a novel feature vector based on physicochemical property of amino acids for prediction protein structural classes. The proposed method is divided into three different stages. First, a discrete time series representation to protein ...
Which is better: holdout or full-sample classifier design?
Is it better to design a classifier and estimate its error on the full sample or to design a classifier on a training subset and estimate its error on the holdout test subset? Full-sample design provides the better classifier; nevertheless, one might ...
Combining evidence, specificity, and proximity towards the normalization of gene ontology terms in text
Structured information provided by manual annotation of proteins with Gene Ontology concepts represents a high-quality reliable data source for the research community. However, a limited scope of proteins is annotated due to the amount of human ...
Inference of gene regulatory networks based on a universal minimum description length
The Boolean network paradigm is a simple and effective way to interpret genomic systems, but discovering the structure of these networks remains a difficult task. The minimum description length (MDL) principle has already been used for inferring genetic ...