CAHNRS researchers employ comprehensive multi-omic strategies to aid in analysis, visualization, and interpretation of big data relevant to sustainable agriculture and natural resource management.
Genomics & Transcriptomics
- Laura Bartley, genomics and transcriptomics of grasses for biofuels
- Maren Friesen, ecological and evolutionary genomics of symbioses
- David Gang, multi-omic analysis of agriculturally important plant species
- Caren Goldberg, population genomics of amphibians
- Norm Lewis, integrated omics approach to plant biochemical evolution
- Holly Neibergs, comparative and functional animal genomics
- John Peters, transcriptomics of microbial physiology
- Michael Phelps, Director of the Thorgaard Center for Salmonid Physiology and Genomics, functional genomics and phenomics of salmonids and other aquatic organisms
- Karen Sanguinet, genomics of root architecture
Metabolomics & Proteomics
- David Gang, Director of the Tissue Imaging, Metabolomics, and Proteomics Laboratory
- Mark Lange, Director of the M.J. Murdock Metabolomics Laboratory Service Center
Plant Phenomics
- Helmut Kirchhoff, Phenomics Center Coordinator
- Dominik Schneider, Phenomics Center Manager
- Kimberly Campbell, wheat research greenhouse phenomics
- Sindhuja Sankaran, field-based phenomics using proximal and remote sensing
- Zhiwu Zhang, high-throughput phenomic data analysis and computation
Bioinformatics
- Stephen Ficklin, cyberinfrastructure supporting transfer, storage, visualization, and analysis of “omics” data sets
- Dorrie Main, computational tools and database resources for crop genomics, genetics, and breeding research
- Zhiwu Zhang, high-throughput “omics” data analysis and computation
Ecoinformatics
- Stephanie Hampton, ecological dynamics in aquatic ecosystems
- Javier Gutierrez Illan, effects of environmental change on biodiversity and pest management from a landscape perspective
- Stephen Katz, ecological communities and ecosystem stability
- Arjan Meddens, forest dynamics analysis using satellite and other geospatial data