The field of gene expression data analysis has grown in the past few years from being
purely data-centric to integrative, aiming at complementing microarray analysis with data …

Modeling the complexity of sickle cell disease pathophysiology and severity is difficult. Using
data from 3380 patients accounting for all common genotypes of sickle cell disease …

Bayesian Networks (BN) have been a popular predictive modeling formalism in
bioinformatics, but their application in modern genomics has been slowed by an inability to …

In this paper, we review the role of probabilistic graphical models in artificial intelligence. We
start by giving an account of the early years when there was important controversy about the …

Compared with expert systems for specific disease diagnosis, knowledge-based systems to
assist decision making in triage usually try to cover a much wider domain but can use a …

To explore novel methods for the analysis of metabolomics data, we compared the ability of
Partial Least Squares Discriminant Analysis (PLS-DA) and Bayesian networks (BN) to build …

The connectivity hub property of the hippocampus (HIP) and the medial prefrontal cortex
(MPFC) is essential for their widespread involvement in cognition; however, the cooperation …

Over the years, research studies have shown there is a key connection between the
microbial community in the gut, genes, and immune system. Understanding this association …

One of the most popular modeling approaches to genetic risk prediction is to use a summary
of risk alleles in the form of an unweighted or a weighted genetic risk score, with weights that …

Inhaled corticosteroids (ICS) are the most commonly used controller medications prescribed
for asthma. Two single-nucleotide polymorphisms (SNPs), rs1876828 in corticotrophin …