Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose a method for automatically discovering reactive motifs, which are motifs discovered from binding and catalytic sites, which incorporate information at binding and catalytic sites with bio-chemical knowledge.  introduce the concept of mutation control that uses amino acid substitution groups and conserved regions to generate complete amino acid substitution groups. Mutation control operations are described and formalized using a concept lattice representation.  show that a concept lattice is efficient for both representations of bio-chemical knowledge and computational support for mutation control operations. Experiments using a C4.5 learning algorithm with reactive motifs as features predict enzyme function with 72% accuracy compared with 67% accuracy using expert-constructed motifs. This suggests that automatically generating reactive motifs are a viable alternative to the time-consuming process of expert-based motifs for enzyme function prediction.
['Kitsana Waiyamai', 'Peera Liewlom', 'Thanapat Kangkachit', 'Thanawin Rakthanmanon']
I am writing a research paper on a idea Concept lattice-based mutation control for reactive motifs discovery
[{"from": "human", "value": "I am writing a research paper on a idea Concept lattice-based mutation control for reactive motifs discovery"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose a method for automatically discovering reactive motifs, which are motifs discovered from binding and catalytic sites, which incorporate information at binding and catalytic sites with bio-chemical knowledge.  introduce the concept of mutation control that uses amino acid substitution groups and conserved regions to generate complete amino acid substitution groups. Mutation control operations are described and formalized using a concept lattice representation.  show that a concept lattice is efficient for both representations of bio-chemical knowledge and computational support for mutation control operations. Experiments using a C4.5 learning algorithm with reactive motifs as features predict enzyme function with 72% accuracy compared with 67% accuracy using expert-constructed motifs. This suggests that automatically generating reactive motifs are a viable alternative to the time-consuming process of expert-based motifs for enzyme function prediction."}]