Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce a class of generalized DNF formulae called wDNF or ighted disjunctive normal form, and present a molecular algorithm that learns a wDNF formula from training examples. Realized in DNA molecules, the wDNF machines have a natural probabilistic semantics, allowing for their application beyond the pure Boolean logical structure of the standard DNF to real-life problems with uncertainty. The potential of the molecular wDNF machines is evaluated on real-life genomics data in simulation. Our empirical results suggest the possibility of building error-resilient molecular computers that are able to learn from data, potentially from t DNA data.
['Byoung-Tak Zhang', 'Ha-Young Jang']
I am writing a research paper on a idea Molecular learning of wDNF formulae
[{"from": "human", "value": "I am writing a research paper on a idea Molecular learning of wDNF formulae"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce a class of generalized DNF formulae called wDNF or ighted disjunctive normal form, and present a molecular algorithm that learns a wDNF formula from training examples. Realized in DNA molecules, the wDNF machines have a natural probabilistic semantics, allowing for their application beyond the pure Boolean logical structure of the standard DNF to real-life problems with uncertainty. The potential of the molecular wDNF machines is evaluated on real-life genomics data in simulation. Our empirical results suggest the possibility of building error-resilient molecular computers that are able to learn from data, potentially from t DNA data."}]