Washington State University has a rich history of fostering the kind of interdisciplinary science that is needed to advance the state of scientific discovery for many of the challenging biological problems of the 21st century.
- Designing innovative algorithmic solutions for data-intensive life sciences applications. Applications include genome assembly and annotation for economically important plant crops, identification of proteins involved in bioenergy, and decoding gene regulatory and protein-protein interaction networks.
- Developing algorithms for microbiology applications including microbial evolution and phylogenetic tree reconstruction, epidemiology, vaccine development, and controlling antibiotic resistance.
- Developing scalable parallel algorithms for data-intensive biological applications using next-generation supercomputers. Target parallel architectures include massively parallel distributed and shared memory supercomputers, cloud computing platforms, and multicore hardware accelerators.
- Developing algorithms for protein and metabolite identification in complex mixtures by high-throughput mass spectrometry.
Research funding comes from the National Science Foundation, National Institutes of Health, Department of Agriculture, and Department of Energy.