The burden of disease of three food-associated heavy metals in clusters in the Danish population - Towards targeted public health strategies.

Lifestyle and sociodemographics are likely to influence dietary patterns, and, as a result, human exposure to chemical contaminants in foods and their associated health impact. We aimed to characterize subgroups of the Danish population based on diet and sociodemographic indicators, and identify those bearing a higher disease burden due to exposure to methylmercury (MeHg), cadmium (Cd) and inorganic arsenic (i-As). We collected dietary, lifestyle, and sociodemographic data on the occurrence of chemical contaminants in foods from Danish surveys.

KinMutRF: a random forest classifier of sequence variants in the human protein kinase superfamily.

Background: The association between aberrant signal processing by protein kinases and human diseases such as cancer was established long time ago. However, understanding the link between sequence variants in the protein kinase superfamily and the mechanistic complex traits at the molecular level remains challenging: cells tolerate most genomic alterations and only a minor fraction disrupt molecular function sufficiently and drive disease.

Results: KinMutRF is a novel random-forest method to automatically identify pathogenic variants in human kinases.