Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes to model protein regulation networks associated with severe acute respiratory syndrome (SARS) for early prediction of SARS. In the approach, specific to a patient group, a regulatory network is simulated using a fully-connected neural network and is optimized towards minimizing a novel energy function that is defined as a measure of disagreement beten the input and output of the network. The nonlinear version of the network is achieved by applying a sigmoid function. Experimental results show that the proposed approaches can capture regulatory patterns associated with SARS and efficiently implement early prediction of SARS.
['Hong-Qiang Wang', 'Hai Long Zhu', 'Chun-Hou Zheng', 'Timothy T.C. Yip', 'William Cs Cho']
I am writing a research paper on a idea MINING PROTEIN REGULATORY RELATIONSHIPS USING NEURAL NETWORK METHODS FOR EARLY PREDICTION OF SARS
[{"from": "human", "value": "I am writing a research paper on a idea MINING PROTEIN REGULATORY RELATIONSHIPS USING NEURAL NETWORK METHODS FOR EARLY PREDICTION OF SARS"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes to model protein regulation networks associated with severe acute respiratory syndrome (SARS) for early prediction of SARS. In the approach, specific to a patient group, a regulatory network is simulated using a fully-connected neural network and is optimized towards minimizing a novel energy function that is defined as a measure of disagreement beten the input and output of the network. The nonlinear version of the network is achieved by applying a sigmoid function. Experimental results show that the proposed approaches can capture regulatory patterns associated with SARS and efficiently implement early prediction of SARS."}]