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 employ a variety of statistical learning methods, ranging from dimensionality reduction, graphical models, and high-dimensional data analysis, to address the analytical challenges faced with interpreting complex health data. The long-term goals of our research are to enhance biomarker discoveries through powerful and robust statistical inference, and to translate these findings to advance clinical research.

Our current research interests include statistical learning, network analysis, and systems biology, 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.


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 to Kun Yue, who who has been named a winner of Best Student Paper for the 2021 WNAR Student Paper Competition!

Her paper “REHE: Fast Variance Components Estimation for Linear Mixed Models” proposes a new method for estimating the variance components in linear mixed models.

Posted 28 Jul 2021 by Jing Ma

Jing received an award from The Pathogen Associated Malignancies Integrated Research Center for the pilot project on “Statistical Methods for Network-based Analysis of the Colorectal Cancer Microbiome”.

This project is in collaboration with on Dr. Amanda Phipps (associate professor of epidemiology, University of Washington, and associate professor in the Public Health Sciences Division), Dr. Sam Minot (associate director of data science applications, Hutch Data Core) and Dr. Neelendu Dey (assistant professor in the Clinical Research Division).

Posted 02 Jul 2021 by Jing Ma

Ilias Moysidis obtained his Ph.D. in Statistics from Penn State University in 2021. Welcome, Ilias!

Posted 21 Jun 2021 by Jing Ma

Congratulations, Yue! Yue has done amazing work in dimensionality reduction of structured microbiome data and high-dimensional inference. Check out his paper here and here.

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
Published 17 Sep 2021
Published 11 Jun 2021
Published 16 Apr 2021
Networks for compositional data
Ma et al. (2021). Statistical Analysis of Microbiome Data.
Published 20 Feb 2021
Published 05 Feb 2021