In this research project computational methods will be developed and applied to predict the structure of Ribonucleic Acid (RNA) molecules from their sequence. Undergraduate students will perform all of the investigations, including the selection of sequences to be investigated, providing them with excellent training and valuable research experience. Students from PI's laboratory have an excellent track record for attending graduate and professional schools after obtaining their BS degrees. Since 2005, 11 of these students are attending graduate school in either chemistry or biochemistry; and, 12 are attending professional school. The graduate programs attended by the students include Yale University, University of Rochester, Penn State University, Duke University, Carnegie Mellon University, Ohio State University, Arizona State University, and University of Illinois Urbana-Champaign. This work will be disseminated as published manuscripts in peer-reviewed journals and at scientific meetings including regional and national meetings. Since 2006, 29 of the PI's students have been co-authors on papers. In the past eight years, 20 students have given presentations at either national or regional meetings. The improvements in secondary structure prediction will be incorporated into RNA structure, a secondary structure prediction program distributed by the Mathews lab (University of Rochester). In addition, a high school science teacher will be recruited to join the research group during the summer. The high school teacher will have the opportunity to engage in authentic research using state-of-the-art techniques, methodology and instrumentation. This, in turn, enhances the teacher's abilities and experience base and makes for a richer teaching and learning experience in high school science classes.
The objective of this project is to develop models to predict the structure of Ribonucleic Acid (RNA) molecules from their sequence. RNAs are intimately involved in a wide variety of biological activities. During the process of gene expression (protein synthesis), they serve as informational molecules and part of the synthesis machinery. Biological molecules, including RNA, must fold into the correct three-dimensional shape to acquire their active-functional form. The ability to predict RNA structure from sequence will improve our understanding of RNA and its biological role. This project will develop models for the prediction of RNA structure from sequence. These studies will combine both stability and structural characterization of RNA to achieve a better understanding of the nature of RNA.
