Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Selection of influential genes using gene expression data from normal and disease samples is an important topic in bioinformatics. ,  propose a novel computational method for the problem, which combines gene expression patterns from normal and disease samples with a mathematical model of metabolic networks. This method seeks a set of k genes knockout of which drives the state of the metabolic network towards that in the disease samples.  adopt a Boolean model of metabolic networks and formulate the problem as a maximization problem under an integer linear programming framework.  applied the proposed method to selection of influential genes using gene expression data from normal samples and disease (head and neck cancer) samples. The result suggests that the proposed method can select more biologically relevant genes than an existing P-value based ranking method can.
['Takeyuki Tamura', 'Tatsuya Akutsu', 'Chun-Yu Lin', 'Jinn-Moon Yang']
I am writing a research paper on a idea Finding Influential Genes Using Gene Expression Data and Boolean Models of Metabolic Networks
[{"from": "human", "value": "I am writing a research paper on a idea Finding Influential Genes Using Gene Expression Data and Boolean Models of Metabolic Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Selection of influential genes using gene expression data from normal and disease samples is an important topic in bioinformatics. ,  propose a novel computational method for the problem, which combines gene expression patterns from normal and disease samples with a mathematical model of metabolic networks. This method seeks a set of k genes knockout of which drives the state of the metabolic network towards that in the disease samples.  adopt a Boolean model of metabolic networks and formulate the problem as a maximization problem under an integer linear programming framework.  applied the proposed method to selection of influential genes using gene expression data from normal samples and disease (head and neck cancer) samples. The result suggests that the proposed method can select more biologically relevant genes than an existing P-value based ranking method can."}]