Background The process of generating raw genome sequence data continues to become
cheaper, faster, and more accurate. However, assembly of such data into high-quality …

Obtaining accurate class prediction of a query object is an important component of
supervised classification. However, it could be also important to understand the …

Gene expression data provide the expression levels of tens of thousands of genes from
several hundred samples. These data are analyzed to detect biomarkers that can be of …

The advance of high-throughput RNA-Sequencing techniques enables researchers to
analyze the complete gene activity in particular cells. From the insights of such analyses …

An understanding towards genetics and epigenetics is essential to cope up with the
paradigm shift which is underway. Personalized medicine and gene therapy will confluence …

Motivation Feature selection approaches are widely used in gene expression data analysis
to identify the most relevant features and boost performance in regression and classification …

High-throughput RNA sequencing produces large gene expression datasets whose analysis
leads to a better understanding of diseases like cancer. The nature of RNA-Seq data poses …

Current Genome-wide advancements in Gene chips technology provide in the “Omics
(genomics, proteomics and transcriptomics) research”, an opportunity to analyze the …

Background Reproducible benchmarking is important for assessing the effectiveness of
novel feature selection approaches applied on gene expression data, especially for prior …

Over the past few decades, to computerized diagnostic tools, intended to aid expert in
making sense out of the welter of data. Due to improvements in biometric instrumentation …