Tianhua (Tim) Niu, MS, ScDTianhua (Tim) Niu, MS, ScD

Tulane University School of Public Health and Tropical Medicine
Assistant Professor, Department of Biostatistics and Bioinformatics

Genetic association, transcriptomics, and pathway analyses of diabetes-related phenotypes


Dr. Tianhua (Tim) Niu is an Assistant Professor at the Department of Biostatistics and Bioinformatics, Tulane University School of Public Health and Tropical Medicine. Before joining Tulane, Dr. Niu has been an Assistant Professor of Psychiatry and Neurobehavioral Sciences, University of Virginia School of Medicine since 2008. Dr. Niu’s research involves development and application of methodologies for analyzing high-dimensional data using various statistical algorithms and computer software programs. During 2002-2008, Dr. Niu was Assistant Professor of Medicine, Harvard Medical School, an Assistant Professor of Epidemiology, Harvard School of Public Health, and the Director of Bioinformatics, Division of Preventive Medicine, Brigham and Women’s Hospital. Dr. Niu is a permanent member of Upsilon Pi Epsilon, International Honor Society in the Computing Sciences, and has been invited as an ad hoc reviewer for NIH applications for health research since 2005. Dr. Niu is a peer reviewer for over 40 leading international journals. To date, Dr. Niu has published 86 original articles and 7 review articles in world’s premier peer-reviewed journals, 9 book chapters including 2 chapters published in two top medical textbooks, “Osteoporosis” and “Principles of Bone Biology” respectively, both by the prestigious publisher - the Academic Press, and a book entitled “Ontologies for Bioinformatics” by the MIT Press. Dr. Niu has been invited to give lectures worldwide, including International Conference on Computational Systems Bioinformatics, the National Research Council of Canada. Dr. Niu has one United States Patent granted in 2005 on Haplotype Determination.

Ongoing research projects related to diabetes-related phenotypes

Diabetes, a complex endocrine disease characterized by hyperglycemia, is emerging as a modern day epidemic. There are two major types of diabetes  type 1 diabetes (T1D), and type 2 diabetes (T2D). T2D accounts for over 90% of diabetic individuals globally, and results from interactions of environmental, nutritional, and genetic factors. Our group is mainly interested in three research areas: (i) identification and functional prediction of genetic variants of T2D and related phenotypes, e.g. obesity and osteoporosis; (ii) detection of significantly differentially expressed genes (including microRNA and long non-coding RNA genes) in the pathogenesis of diabetes and related disorders, and (iii) pathway analysis of association signals at genetic and transcriptomic levels that considers cumulative effects (or enrichments) of a group of variants or genes on the particular phenotype of interest. We employ a plethora of biostatistical and bioinformatics software tools to analyze both genomics and transcriptomics data from both humans and animal models. The field of computational biology has expanded at a rapid pace. Graduate students and research fellows are trained to gain abundant experience and to apply a wide range of effective biostatistical and bioinformatics methods to discover the fundamental principles that determine the relationship between gene functions and phenotypes.

Ongoing projects include:

  1. Bioinformatics analysis of transcriptomics study in mice with conditional knockouts of the estrogen or/and androgen receptors;
  2. Roles of molecular variants in genes of insulin secretion and insulin signaling pathways in T2D etiology;
  3. Roles of multifunctional adipose tissue-derived cytokines in T2D pathogenesis; and
  4. Roles of genetic polymorphisms in determining therapeutic responses in treatment of T2D.

Lab Member

Tao Yang, PhD student, Department of Biostatistics and Bioinformatics

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