CU Department of Biomedical Informatics

Understanding how our genes shape traits & diseases is a huge challenge. Traditional studies link DNA changes to gene activity but often miss how genes interact.

Enter PhenoPLIER—a powerful tool using machine learning to group genes based on co-expression & drug responses. This approach helps uncover hidden gene networks, making genetic studies more insightful & leading to personalized medicine breakthroughs!

Genetic studies through the lens of gene networks When citing this paper, please use the following: Subirana-Granés M, Hoffman J, Zhang H, Akirtava C, Nandi S, Fotso K, Pividori M. Genetic studies through the lens of gene networks. 2025. Annu. Rev. Biomed. Data Sci. 8. https://doi.org/10.1146/annurev-biodatasci-103123-095355

“Our ultimate goal is to discover the biological mechanisms relevant to women’s health and that underlie s*x differences across health and disease so we can translate this new knowledge into improved health for all.” — Barbara Stranger, PhD, professor of biomedical informatics, Lyda M. Ludeman Endowed Chair in Bioinformatics in Women’s Health Research.

✨ National Women’s Health Week (NWHW) is here! Every May, starting on Mother's Day, the U.S. Department of Health and Human Services (HHS), Office on Women's Health (OWH) leads this observance to empower women to prioritize their health. This year, from May 11-17, join us in highlighting key health issues, encouraging self-care, and championing well-being at every stage of life.

Barbara Stranger, PhD, Joins DBMI Faculty as Endowed Chair for Women’s Health Barbara Stranger, PhD, and her lab will dive deep into data to learn more about genetic variations between s*xes and how that translates into disease phenotypes.

Exciting advancements in genetics! A recent study has revealed that some areas of our DNA mutate at unprecedented rates, offering new insights into human evolution and genetic diseases. This groundbreaking research, published in Nature, utilized advanced sequencing technologies to map genetic changes across generations. Such discoveries not only deepen our understanding of what makes us human but also pave the way for improved genetic counseling and disease prevention.

Human de novo mutation rates from a four-generation pedigree reference - Nature Analysis of more than 95% of each diploid human genome of a four-generation, twenty-eight-member family using five complementary short-read and long-read sequencing technologies provides a truth set to understand the most fundamental processes underlying human genetic variation.

📍 Where medicine, computational techniques and a clear vision come together to make life-changing progress.