Developing statistical methods for analysis of complex traits
Advancing mass spectrometer technology by developing instrumentation, chemistry, & informatics
Creating machine-learning methods for inferring networks of interacting genes, proteins, environmental variables, and phenotypes
Developing statistical and algorithmic approaches for the analysis of biological sequence data
Gasch, Audrey P.
Elucidating systems-level relationships between genotype-phenotype-environment in eukaryotic stress responses
Hittinger, Chris Todd
The Hittinger Lab uses yeast carbon metabolism as a model for basic bioenergy, biomedical, and evolutionary research
Developing statistical genomic methods, especially with regard to noncoding regulatory sequences and effects of their variation
Innovating statistical methods for the analysis of high-throughput genomics data, including bulk and single-cell transcriptomic measurements
A bioengineering approach to understanding fundamental biological and medical questions in microbes, specifically model and pathogenic yeasts.
Newton, Michael A.
Developing statistics and empirical Bayes methods for contemporary biomedical applications