Statistical Genomics at UW-Madison


Statistical Genomics concerns the application of statistical methods to problems in genomics (and genetics and molecular biology).

The University of Wisconsin - Madison has a large complement of statistical genomics faculty in multiple departments and wealth of opportunities for research and education in the field.


Courses Software Students
 
Prospective Students


Faculty

Cécile Ané
Associate Professor
Statistics and Botany
Statistical inference in molecular evolution; model selection; inference on the distribution of genealogies across the genome; analysis of trait evolution using phylogenetic trees.
 
Karl Broman
Professor
Biostatistics & Medical Informatics
Characterization of meiotic recombination and the development of improved methods for detecting and identifying genes contributing to variation in complex traits in humans and experimental organisms.
 
Natalia de-Leon
Assistant Professor
Agronomy
Plant breeding and quantitative genetics. Population enhancement for biomass increase and cell wall composition. Interface of plant breeding and quantitative and molecular genetics. Combination of different sources of genetic information such as phenotypic, genotypic and expression data. Genetic analysis of developmental traits in maize.
 
Daniel Gianola
Professor
Animal Sciences, Biostatistics & Medical Informatics, and Dairy Science
Statistical problems in quantitative genetics and animal breeding; Bayesian approaches for inference about parameters of linear and nonlinear models (e.g., for growth and lactation curves), censored (e.g., productive lifespan) and discrete (e.g., fertility and viability) distributions. International animal breeding and biometry.
 
Sunduz Keles
Associate Professor
Biostatistics & Medical Informatics and Statistics
Developing and applying statistial methods for problems that arise in genome biology.
 
Christina Kendziorski
Associate Professor
Biostatistics & Medical Informatics
Methods and software for the analysis of data from high-throughput studies of genetics and genomics, particularly ion studies of complex diseases.
 
Bret Larget
Associate Professor
Statistics and Botany
Phylogenetics and molecular evolution
 
Michael Newton
Professor
Biostatistics & Medical Informatics and Statistics
Statistical problems in the analysis of gene expression microarrays and other high-throughput genomic technologies.
 
Guiherme Rosa
Associate Professor
Animal Sciences and Biostatistics & Medical Informatics

Research at the interface between statistical/theoretical and molecular genetics, focusing on applications to animal models in domestic/managed and natural populations.
 
Grace Wahba
Professor
Statistics, Biostatistics & Medical Informatics, and Computer Sciences
Multivariate function estimation and statistical model building, with emphasis on statistical theory and the development of efficient numerical and statistical methods for large and extremely large data sets, and applications to biostatistics, numerical weather prediction, climate, and supervised machine learning.
 
Sijian Wang
Assistant Professor
Biostatistics & Medical Informatics and Statistics
High-dimensional data analysis, variable selection and model selection; bioinformatics; machine learning and data mining; statistical modeling in medical sciences.
 
Kent Weigel
Professor
Dairy Science
Genetic improvement of dairy cattle using whole genome selection, low-density genotyping, imputation of missing genotypes, inbreeding management tools, and genome-guided mate selection algorithms.
 
Brian Yandell
Professor
Statistics and Horticulture
Unraveling the complex relationships between observeable traits (such as flowering time or clinical signs of diabetes) and molecular signals (mRNA expression, protein and metabolite levels, etc.); development of informatics platforms that allow biologists and data analysts to share data and algorithms.


Web maintainer: Karl Broman Last modified: Wed Mar 21 11:51:31 2012