Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Recent work in computational structural biology focuses on modeling intrinsically dynamic proteins important to human biology and health. The energy landscapes of these proteins are rich in minima that correspond to alternative structures with which a dynamic protein binds to molecular partners in the cell. On such landscapes, evolutionary algorithms that switch their objective from classic optimization to mapping are more informative of protein structure function relationships. While techniques for mapping energy landscapes have been developed in computational chemistry and physics, protein landscapes are more difficult for mapping due to their high dimensionality and multimodality. ,  describe a memetic evolutionary algorithm that is capable of efficiently mapping complex landscapes. In conjunction with a hall of fame mechanism, the algorithm makes use of a novel, lineage- and neighborhood-aware local search procedure or better exploration and mapping of complex landscapes.  evaluate the algorithm on several benchmark problems and demonstrate the superiority of the novel local search mechanism. In addition,  illustrate its effectiveness in mapping the complex multimodal landscape of an intrinsically dynamic protein important to human health.
['Emmanuel Sapin', 'Kenneth A. De Jong', 'Amarda Shehu']
I am writing a research paper on a idea A Novel EA-based Memetic Approach for Efficiently Mapping Complex Fitness Landscapes
[{"from": "human", "value": "I am writing a research paper on a idea A Novel EA-based Memetic Approach for Efficiently Mapping Complex Fitness Landscapes"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Recent work in computational structural biology focuses on modeling intrinsically dynamic proteins important to human biology and health. The energy landscapes of these proteins are rich in minima that correspond to alternative structures with which a dynamic protein binds to molecular partners in the cell. On such landscapes, evolutionary algorithms that switch their objective from classic optimization to mapping are more informative of protein structure function relationships. While techniques for mapping energy landscapes have been developed in computational chemistry and physics, protein landscapes are more difficult for mapping due to their high dimensionality and multimodality. ,  describe a memetic evolutionary algorithm that is capable of efficiently mapping complex landscapes. In conjunction with a hall of fame mechanism, the algorithm makes use of a novel, lineage- and neighborhood-aware local search procedure or better exploration and mapping of complex landscapes.  evaluate the algorithm on several benchmark problems and demonstrate the superiority of the novel local search mechanism. In addition,  illustrate its effectiveness in mapping the complex multimodal landscape of an intrinsically dynamic protein important to human health."}]