Goals: The major focus of this RII Track-1 project is the merging of biology and chemistry through computational investigation and simulation. The project seeks to do this by 1) linking molecular modeling to macroscale physiology, 2) deploying high-level data mining, and 3) modeling nanoscale structures to understand binding interactions and catalytic processes. The biological simulation efforts are broad, ranging from whole body physiological modeling methods to specific modeling of problems such as particle deposition in upper lung airways. The computational biology effort centers on developing new methods for integrating functional genomics information from high-throughput sources such as microarrays and next generation gene sequencers. The computational chemistry effort is geared towards theoretical characterization of nanomaterials for sensor technologies, and the development of models to predict the effects of nanomaterials on health and the environment.
This project seeks to capitalize on previous Research Infrastructure Improvement (RII) investments by strengthening the quality of research in each of the research foci, increasing the statewide collaborations in each area, and establishing meaningful collaborations in the emerging research areas. Underpinning all of the research components are the establishment of needed cyberinfrastructure and the integration of education at all levels.
Intellectual Merit This project will integrate research in modeling and simulation of complex systems to advance the understanding of complex biological systems and networks, and the understanding of the effects of nanoparticles on specific functions of the biological systems/networks. As such the projects focus on problems of practical significance (simulation of inhalation exposure to nanoparticles and the resulting deleterious effects on respiratory and cardiovascular function); propose new models for learning biological networks that combine Bayesian learning and numerical optimization and can lead to novel approaches for explaining model response; and explore new theoretical characterization of nanoscale materials with particular emphasis on using quantum mechanics (QM) to predict changes in structure and electronic properties of nanomaterials for sensors, and use Quantitative Structure-Property Relationship (QSPR) and Quantitative Structure-Activity Relationship (QSAR) models to predict nanotoxicity.
Broader Impacts This project will impact the diversity of the computational sciences community of faculty and students in Mississippi and contribute to the development of a skilled workforce that will assist Mississippi in transitioning to a knowledge-based economy. It will also contribute to the broader computational sciences community by investigating specific complex biological systems and processes with significant societal impact.
