CAREER: Global Self-Organization of all Known Proteins - Toward a Complete Map of the Protein Space

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EIA-0133311Golan YonaCornell UniversityCAREER: Global Self-Organization of all Known Proteins - Toward a Complete Map of the Protein SpaceThis effort addresses the growing need to characterize and organize all known proteins (the protein space) into functional classes. This effort will develop sensitive algorithms to detect subtle relationships between proteins and protein families, and will study and develop new techniques for representing the protein space as a mathematical object that can be further explored. Additionally, it will develop new unsupervised learning techniques for studying the properties and geometry of the protein space, and eventually to create a complete road map of the protein space.The outcome proposed will be a complete, accurate map of the protein universe. A direct benefit of the map is the ability to automatically classify every protein; known proteins as well as new proteins that will be sequenced in the future. This map can indicate the possible function of newly determined sequences that cannot be deciphered by traditional methods, based on the relative position of the sequence in the space. It can expose new relationships between distantly related protein families, limit the possible structural conformations of sequences and explain the mapping of sequences to structures, and may add insights about fundamental evolutionary processes.