Genes are at the center of nearly every human disease and symptom, and until the past few decades, medical researchers had a much narrower interpretation of the human body’s entire genetic makeup, also called the genome.
“Should I be taking a probiotic?” is a question that Maggie Stanislawski, PhD, assistant professor in the University of Colorado Department of Biomedical Informatics (DBMI), gets asked often.
Anybody who has ever experienced altitude sickness, even the mildest form known as acute mountain sickness, knows how debilitating it can be. Symptoms, which include lightheadedness, nausea, fatigue, and headache, most often occur at altitudes above 8,000 feet.
With no cure or widely successful therapeutic options for patients with rheumatoid arthritis (RA), Fan Zhang, PhD, is looking to computational machine learning to identify new target treatments.
Following an analysis of more than 20,000 articles by researchers in the Department of Biomedical Informatics (DBMI) at the University of Colorado School of Medicine, a major science publication is implementing new policies to improve the diversity of its sources.
Transcriptome-wide association studies have helped uncover the role of individual genes in disease-relevant mechanisms, explain researchers from the CU Department of Biomedical Informatics. However, modern models of the architecture of complex traits predict that gene-gene interactions play a crucial role in disease origin and progression. Researchers introduce PhenoPLIER, a computational approach that maps gene-trait associations and pharmacological perturbation data into a common latent representation for a joint analysis and observe that diseases are significantly associated with gene modules expressed in relevant cell types, and our approach is accurate in predicting known drug-disease pairs and inferring mechanisms of action.
After tracking calorie-control dieters and intermittent fasters for three months, both had improved microbiome diversity, said study author Maggie Stanislawski, an assistant professor in the CU Department of Biomedical Informatics.
DBMI geneticist Joanne Cole, PhD, explains the role of genetics and other factors in food preference.
Researchers in the CU Department of Biomedical Informatics evaluate associations among gut microbiota (MB), DNA methylation (DNAme), and diet prior to and during a behavioral weight loss intervention.