Statistical Learning for Big Biomedical Data

The Ma Lab at Fred Hutchinson Cancer Research Center specializes in statistical and computational methods for big biomedical data. We address statistical challenges faced with understanding and interpreting complex health data, and develop novel statistical methods to enhance reproducible biomedical discoveries. Our current research interests include microbiome data analysis and statistical data integration with applications to cancer biology and aging.

Our lab collaborates with Dr. Daniel Promislow on the Dog Aging Project, supported by U19 grant AG057377 from the National Institute of Aging, a part of the National Institutes of Health.

Postdoc Position Available

Advising: We are recruiting motivated and hard-working students interested in statistical learning for bimedical data. If you are an undergrad or graduate student at the University of Washington, and you are interested in any of the papers or projects listed on this website, send me an email with your interests and CV.

Congratulations, Yue!

Posted 15 Aug 2020 by Jing Ma

We are looking for dogs for the largest-ever study of aging in canines! You can find out more about the Dog Aging Project here or from this article in New York Times.

Posted 20 Nov 2019 by Jing Ma

I will be visiting Department of Statistics at Texas A&M University as Assistant Professor, during the academic year 2019-2020.

Posted 05 Aug 2019 by Jing Ma

Joint work with Drs. Alla Karnovsky, Farsad Afshinnia and George Michailidis on differential network enrichment analysis is featured at Fred Hutch Science Spotlight.

Posted 20 May 2019 by Jing Ma

Jing received award from The Jayne Koskinas Ted Giovanis Foundation for Health and Policy, joint with Minjoung Kyoung, Michael Konopka, Tara Sigdel, Young Hwan Chang on a proposal titled ``Understanding Therapeutics Failures Through 4D Single-cell Analysis of Metabolic Heterogeneityā€¯.

Posted 25 Jul 2018 by Jing Ma