In the past decade, significant progress has been made in complex disease research across
multiple omics layers from genome, transcriptome and proteome to metabolome. There is an …

Following the identification of several disease-associated polymorphisms by genome-wide
association (GWA) analysis, interest is now focusing on the detection of effects that, owing to …

Background The selection, development, or comparison of machine learning methods in
data mining can be a difficult task based on the target problem and goals of a particular …

Of the various attempts to generalize information theory to multiple variables, the most
widely utilized, interaction information, suffers from the problem that it is sometimes negative …

BACKGROUND: The widespread availability of new computational methods and tools for
data analysis and predictive modeling requires medical informatics researchers and …

Genome-wide association studies (GWAS) have rapidly become a standard method for
disease gene discovery. A substantial number of recent GWAS indicate that for most …

Motivation: The sequencing of the human genome has made it possible to identify an
informative set of> 1 million single nucleotide polymorphisms (SNPs) across the genome …

The determination of gene-by-gene and gene-by-environment interactions has long been
one of the greatest challenges in genetics. The traditional methods are typically inadequate …

Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are
growing in popularity. Their versatility and modelling power is now employed across a …

Multifactor dimensionality reduction (MDR) was developed as a method for detecting
statistical patterns of epistasis. The overall goal of MDR is to change the representation …