DNA microarray experiments generating thousands of gene expression measurements, are
used to collect information from tissue and cell samples regarding gene expression …

In the past several years, experiments using DNA microarrays have contributed to an
increasingly refined molecular taxonomy of hematologic malignancies. In addition to the …

We propose in this paper a very fast feature selection technique based on conditional
mutual information. By picking features which maximize their mutual information with the …

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

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

In the field of statistical discrimination k-nearest neighbor classification is a well-known, easy
and successful method. In this paper we present an extended version of this technique …

Support vector machines (SVMs) were used to develop QSAR models that correlate
molecular structures to their toxicity and bioactivities. The performance and predictive ability …

There is growing interest in the application of machine learning techniques in bioinformatics.
The supervised machine learning approach has been widely applied to bioinformatics and …

Partial Least Squares (PLS) dimension reduction is known to give good prediction accuracy
in the context of classification with high-dimensional microarray data. In this paper, the …

We report a novel, proof-of-concept, computational method that models a type of brain
cancer (glioma) only by using the topological properties of its cells in the tissue image. From …