To test this prediction, we first utilized computational methods to predict conserved fRNA secondary structures within multiple species alignments of Saccharomyces sensu strico genomes.
Systematic screens for sRNAs have focused mostly on intergenic regions and utilized computational methods [ 5– 10], shotgun cloning strategies [ 11, 12] and high-density oligonucleotide probe arrays [ 13– 15].
We therefore utilized computational methods to test the hypothesis that some of the genes within this large up-regulated cluster are co-ordinately regulated by common transcriptional mechanisms.
Our current research effort focuses on full-length three-dimensional structures of the R-subunit, utilizing computational and bioinformatics methods.
CAMM also utilizes computational linguistics methods for comparison of clinical annotations from multiple datasets.
Our method utilizes computational predictions of protein-ligand binding across the human proteome.
All projects utilize computational modeling combined with microfabricated, patient-derived and physiologically relevant culture platforms and advanced imaging approaches.
We utilized computational approaches to identify new candidate recruiters.
The framework utilizes novel computational methods which enable evaluating the model fragility with respect to quantitative performance measures and parameters such as reaction rate constants and initial conditions.
We develop and utilize computational tools (molecular dynamics statistical methods, electronic structure, materials informatics approaches, etc). and interact closely with experimentalists.
Dr. Lee has over 15 years of experience in industry and academia in public health operations research, which involves developing and utilizing mathematical and computational methods, models, and tools to help stakeholders better understand decision making, processes, and systems.
