Using Genotype-Tissue Expression project samples, researchers put together gene regulatory networks for 29 tissue types, uncovering extensive sex-related regulatory differences.
Backed by BARDA, Merck and Institute for Systems Biology are studying multiomic data to understand infection pathways and find biomarkers for symptom risk.
This new partnership between Harvard's Chan School of Public Health and the Human Vaccines Project seeks to apply AI and genomics to accelerate vaccine development.
Using systems biology, investigators put cancer risk SNPs in a network context, identifying immune, tumor-related, and other genes influenced by the variants in multiple tissue types.
The company uses systems biology approaches and AI methods to model and analyze causal pathways in diseases including neurological cancers and Alzheimers.
A large genome-wide association meta-analysis and follow-up analyses revealed eight risk loci involving SNPs previously associated with body traits, metabolism, and psychiatric risk.
Researchers brought together blood transcriptomic, metabolomic, proteomic, and immune cell profiles for dozens of West African and Australasian infants.
Using omics and other data, researchers performed network analyses that pointed to interactions between human herpesviruses and other Alzheimer's disease risk factors.
Through a genome-wide association study, meta-analysis, and systems analysis, researchers saw enhanced common variant distribution in mutation-intolerant genes.
Using pathway and network analyses, researchers identified overlapping genes and biological processes behind smoking and schizophrenia, including new candidate genes.
