Essential genes are indispensable for an organism’s living. These genes are widely discussed, and many researchers proposed prediction methods that not only find essential genes but also assist pathogens discovery and drug development. However, few studies utilized the relationship between gene functions and essential genes for essential gene prediction. In this paper, we explore the topic of e...

One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theor...

Hidden Markov models [2] (HMMs) have been successfully applied to Bioinformatics such as gene finding, remote homology detection and secondary structure prediction. On the other hand, continuous density HMMs have been widely used in the field of speech recognition. Though continuous density HMMs were not applied to Bioinformatics so far, they may also be useful in Bioinformatics. Currently, we ...

A cDNA microarray is a complex biochemical-optical system whose purpose is the simultaneous measurement of gene expression for thousands of genes. In this paper we propose a general statistical approach to finding associations between the expression patterns of genes via the coefficient of determination. This coefficient measures the degree to which the transcriptional levels of an observed gen...

Different data sources have been used to learn gene function. Whereas combining heterogeneous data sets to infer gene function has been widely studied, there is no empirical comparison to determine the relative effectiveness or usefulness of different types of data in terms of gene function prediction. In this paper, we report a comparative study of yeast gene function prediction using differen...

The genetic codon UGA has a dual function: serving as a terminator and encoding selenocysteine. However, most popular gene annotation programs only take it as a stop signal, resulting in misannotation or completely missing selenoprotein genes. We developed a computational method named Asec-Prediction that is specific for the prediction of archaeal selenoprotein genes. To evaluate its effectiven...