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Barbara E. Stranger on Muck Rack

Barbara E. Stranger

As seen in: Nature, BioRxiv, Cell Press
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Articles

A National Institute on Aging workshop on sex differences in health across the lifespan

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By Jeffrey Pea, Siobhan Addie, Fabrisia Ambrosio, Rozalyn Anderson, C. Noel Bairey Merz, Elizabeth Barr, Stacy Carrington-Lawrence, Rafael de Cabo, Patrice Desvigne-Nickens, Dena B. Dubal, Chelsea M. Haakenson, Emily Jacobs, Maja Marić, Jennifer Pluznick, Mercy R. PrabhuDas, Marta Rodríguez-García, Michael Stout, Barbara E. Stranger, Dan Theodorescu, John Williams, Fei Wang, Xin Yuan, Viviana Perez, Francesca E Duncan, Passley Hargove-Grimes, Mihoko Kai, Sunila G. Nair, Kristy Nicks, Kimberlee Potter, Susan Taymans
| Nature Verified
In December 2025, the Division of Aging Biology, National Institute on Aging (NIA) at the National Institutes of Health (NIH), in collaboration with staff from other NIA divisions, NIH institutes and the Veterans Health Administration, convened a workshop to explore the mechanistic bases and health effects of sex differences across tissues and ages. Novel research discoveries, technologies and visions to advance sex-differences research were discussed.
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Deciphering the Genetic Underlying Causes of Sex Differences in Multiple Myeloma Incidence and Mortality

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By Yuting Shan, Yingbo Huang, Barbara E. Stranger, Rong Huang, Ajibola Opakunle
| Cell Press Verified
Affiliations & Notes 1Department of Molecular Pharmacology & Therapeutics, Medical School, University of Minnesota, Minneapolis, MN, USA, 55455 2Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA, 55455 3Department of Pharmacology, Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA, 60611 4Department of Biomedical Informatics, School of Medicine, University of Colorado...
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Uncovering hidden gene-trait patterns through biclustering analysis of the UK Biobank

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By Milton Pividori, Suraju Sadeeq, Arjun Krishnan, Barbara E. Stranger
| BioRxiv
Abstract The growing availability of genome-wide association studies (GWAS) and large-scale biobanks provides an unprecedented opportunity to explore the genetic basis of complex traits and diseases. However, with this vast amount of data comes the challenge of interpreting numerous associations across thousands of traits, especially given the high polygenicity and pleiotropy underlying complex phenotypes.
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