Bioinformatics & Statistical Genetics
When the BRC at NC State University was founded in 2000, it was with the understanding that quantitative methods applied to massive datasets are essential to the comprehension of the genomic structure of even the simplest organisms.
The university is located in Raleigh, the heart of one of the leading research areas in the United States. The BRC has developed strong relationships with industrial partners and other academic or government organizations in the Research Triangle Park area.
- Detection of gene-gene interactions using multistage sparse and low-rank regression. Finding an efficient and computationally feasible approach to deal with the curse of high-dimensionality is a daunting challenge faced by modern biological science. The problem becomes even more severe when the interactions are the research focus. To improve the performance of statistical analyses, we propose a sparse and low-rank (SLR) screening based on the combination of a low-rank interaction model and the Lasso screening.
- Integrated Model of Chemical Perturbations of a Biological Pathway Using 18 In Vitro High Throughput Screening Assays for the Estrogen Receptor. We demonstrate a computational network model that integrates 18 in vitro, high-throughput screening assays measuring estrogen receptor (ER) binding, dimerization, chromatin binding, transcriptional activation and ER-dependent cell proliferation.
- EVOLUTION. Fruit flies diversify their offspring in response to parasite infection. The evolution of sexual reproduction is often explained by Red Queen dynamics: Organisms must continually evolve to maintain fitness relative to interacting organisms, such as parasites. Recombination accompanies sexual reproduction and helps diversify an organism's offspring, so that parasites cannot exploit static host genotypes.