Feature selection techniques have become an apparent need in many bioinformatics
applications. In addition to the large pool of techniques that have already been developed in …

Supervised feature selection research has a long history. Its popularity exploded in the past
30 years due to the advance of information technology and the need to analyze high …

A detailed overview of current research in kernel methods and their application to
computational biology. Modern machine learning techniques are proving to be extremely …

This paper studies the problem of building multiclass classifiers for tissue classification
based on gene expression. The recent development of microarray technologies has …

Contemporary biological technologies produce extremely high-dimensional data sets from
which to design classifiers, with 20,000 or more potential features being common place. In …

Subjects with mild cognitive impairment (MCI) have an increased risk to develop Alzheimer's
disease (AD). Voxel-based MRI studies have demonstrated that widely distributed cortical …

A DNA microarray can track the expression levels of thousands of genes simultaneously.
Previous research has demonstrated that this technology can be useful in the classification …

Given a sample covariance matrix, we examine the problem of maximizing the variance
explained by a linear combination of the input variables while constraining the number of …

Stream computing is becoming a more and more popular paradigm as it enables the real-
time promise of data analytics. Apache Kafka is currently the most popular framework used …

Background In the clinical context, samples assayed by microarray are often classified by
cell line or tumour type and it is of interest to discover a set of genes that can be used as …