ITR - ASE - Sim: Iterative Algorithms for solving Difficult Inverse Problems

Cornell University, Ithaca NY

Investigators

Abstract

This award was made on a proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." It supports a pilot project of computational research and algorithmic development on inverse problems with a focus on protein folding. The work may lead to broad applications in condensed matter physics and in other disciplines. Inverse problems are frequently encountered in science and engineering, and especially difficult ones -one-way functions-are exploited in cryptography and data security schemes. Two important examples are the recovery of molecular structure from x-ray diffraction data and factoring the modulus in RSA cryptosystems. As investigations of matter increase in complexity and alternative one-way functions are explored for information security, there is a greater need for efficient and general-purpose algorithms for solving difficult inverse problems. This project will further develop a promising, recently discovered algorithm with an eye to one of the most challenging inverse problems in biology, protein structure prediction from primary sequence data. The new algorithm is a significant departure from the optimization strategies used in the past, which do not exploit the highly designed nature of the protein's energy landscape. The PI aims to demonstrate the advantages of this algorithm over more traditional optimization algorithms. This project will focus on folding model proteins. The PI also aims to implement the key operations of the algorithm for realistic protein potentials. The next generation of scientists and engineers will likely increasingly rely on shared databases and standardized computing protocols in the conduct of their work. The PI aims to develop a miniature realization of such a work environment called "semiprotein world" for Ithaca area high school students. Semiproteins are model proteins with highly simplified properties, but which pose many of the same challenges posed by real proteins. Through a collection of software tools, including a web-based semiprotein data bank, semiprofessional researchers with web access will be able to design and fold semiproteins, and then deposit their findings in the database. The design of semiprotein world will involve on-site participation of Ithaca area high school students and undergraduates in the Cornell Center for Materials Research NSF-REU program. This award also helps support the PI's pilot efforts in developing this outreach program. %%% This award was made on a proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." It supports computational research and algorithmic development on inverse problems with a focus on protein folding. The work may lead to broad applications in condensed matter physics and in other disciplines. Inverse problems are frequently encountered in science and engineering, and especially difficult ones -one-way functions-are exploited in cryptography and data security schemes. Two important examples are the recovery of molecular structure information from x-ray diffraction data and factoring in cryptography. As investigations of matter increase in complexity and new one-way functions are explored for information security, there is a greater need for efficient and general-purpose algorithms for solving difficult inverse problems. This project will further develop a promising, recently discovered algorithm with an eye to one of the most challenging inverse problems in biology, protein structure prediction from primary sequence data. The new algorithm is a significant departure from traditional optimization algorithms. The PI aims to demonstrate the advantages of his new algorithm. This project will focus on folding model proteins and laying the foundations for more realistic protein models. The next generation of scientists and engineers will likely increasingly rely on shared databases and standardized computing protocols in the conduct of their work. The PI aims to develop a miniature realization of such a work environment called "semiprotein world" for Ithaca area high school students. Semiproteins are model proteins with highly simplified properties, but which pose many of the same challenges posed by real proteins. Through a collection of software tools, including a web-based semiprotein data bank, semiprofessional researchers with web access will be able to design and fold semiproteins, and then deposit their findings in the database. The design of semiprotein world will involve on-site participation of Ithaca area high school students and undergraduates in the Cornell Center for Materials Research NSF-REU program. This award also helps support the PI's pilot efforts in developing this outreach program. ***