ABSTRACT Support Vector Machines (SVMs) and related kernel methods have become
increasingly popular tools for data mining tasks such as classification, regression, and …

Background Cancer diagnosis and clinical outcome prediction are among the most
important emerging applications of gene expression microarray technology with several …

Instead of a standard support vector machine (SVM) that classifies points by assigning them
to one of two disjoint half-spaces, points are classified by assigning them to the closest of …

Two-category support vector machines (SVM) have been very popular in the machine
learning community for classification problems. Solving multicategory problems by a series …

Nonalcoholic steatohepatitis (NASH) is a condition which can progress to cirrhosis and
hepatocellular carcinoma. Markers for NASH diagnosis are still lacking. We performed a …

Microarray experiments are providing unprecedented quantities of genome-wide data on
gene-expression patterns. Although this technique has been enthusiastically developed and …

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

Motivation: Cancer diagnosis is one of the most important emerging clinical applications of
gene expression microarray technology. We are seeking to develop a computer system for …

We investigated the role of microRNAs (miRNAs) in the pathogenesis of human
hepatocellular carcinoma (HCC). A genome-wide miRNA microarray was used to identify …

Severe weather-induced power outages affect millions of people and cost billions of dollars
of economic losses each year. The National Association of Regulatory Utility Commissioners …