Jing Ma

Principal Investigator

Fred Hutch
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I am an Associate Professor of Biostatistics at the Fred Hutchinson Cancer Center within the Public Health Sciences Division. I am also an Affiliate faculty in the Department of Biostatistics at the University of Washington. I am broadly interested in network biology and high-dimensional data analysis, motivated by important problems in microbiome science. My work has appeared in Annals of Statistics, Annals of Applied Statistics, Biometrika, Bioinformatics, among many other peer-reviewed journals. I received my bachelor’s degree in Mathematics from Fudan University and my Ph.D. in Statistics from University of Michigan where I worked under the supervision of Dr. George Michailidis. Before coming to Fred Hutch, I was a postdoctoral fellow with Dr. Hongzhe Li and Dr. Tony Cai at the University of Pennsylvania.

My Chinese name is 马静. I am originally from Shangqiu, an ancient city in central China.

Public Health Sciences Division
Fred Hutchinson Cancer Center
1100 Fairview Ave N., Mail Stop M3-B232
Seattle, WA 98109


Generalized matrix decomposition regression estimation and inference for two-way structured data

Regression and classification of compositional data via a novel supervised log ratio method

Once-daily feeding is associated with better health in companion dogs results from the Dog Aging Project

An open science study of ageing in companion dogs

Direct estimation of differential Granger causality between two high-dimensional time series

netgsa Fast computation and interactive visualization for topology-based pathway enrichment analysis

Networks for compositional data

REHE fast variance components estimation for linear mixed models

Joint microbial and metabolite network estimation with the censored Gaussian graphical model

Epigenetic loss of AOX1 expression via EZH2 leads to metabolic deregulations and promotes bladder cancer progression

The generalized matrix decomposition biplot and its application to microbiome data

A comparative study of topology-based pathway enrichment analysis methods

Differential Markov random field analysis with applications to detecting differential microbial community networks

Differential network enrichment analysis reveals novel lipid pathways in Chronic Kidney Disease

CHIME clustering of high-dimensional Gaussian mixtures with EM algorithm and its optimality

Graphical models in genetics, genomics and metagenomics

Network-based pathway enrichment analysis with incomplete network information

Integrative pathway analysis of metabolic signature in bladder cancer a Linkage to The Cancer Genome Atlas project and prediction of survival

Joint structural estimation of multiple graphical models