Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Regulatory sequence detection is a critical facet for understanding the cell mechanisms in order to coordinate the response to stimuli. Protein synthesis involves the binding of a transcription factor to specific sequences in a process related to the gene expression initiation. A characteristic of this binding process is that the same factor binds with different sequences placed along all genome. Thus, any computational approach shows many difficulties related with this variability observed from the binding sequences.  proposes the detection of transcription factor binding sites based on a parametric uncertainty measurement (Renyi entropy). This detection algorithm evaluates the variation on the total Renyi entropy of a set of sequences when a candidate sequence is assumed to be a true binding site belonging to the set. The efficiency of the method is measured in form of receiver operating characteristic (ROC) curves on different transcription factors from  Saccharomyces cerevisiae  organism. The results are compared with other known motif detection algorithms such as Motif Discovery scan (MDscan) and multiple expectation-maximization (EM) for motif elicitation (MEME).
['Joan Maynou', 'Joan-Josep Gallardo-Chacón', 'Montserrat Vallverdú', 'Pere Caminal', 'Alexandre Perera']
I am writing a research paper on a idea Computational Detection of Transcription Factor Binding Sites Through Differential Rényi Entropy
[{"from": "human", "value": "I am writing a research paper on a idea Computational Detection of Transcription Factor Binding Sites Through Differential R\u00e9nyi Entropy"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Regulatory sequence detection is a critical facet for understanding the cell mechanisms in order to coordinate the response to stimuli. Protein synthesis involves the binding of a transcription factor to specific sequences in a process related to the gene expression initiation. A characteristic of this binding process is that the same factor binds with different sequences placed along all genome. Thus, any computational approach shows many difficulties related with this variability observed from the binding sequences.  proposes the detection of transcription factor binding sites based on a parametric uncertainty measurement (Renyi entropy). This detection algorithm evaluates the variation on the total Renyi entropy of a set of sequences when a candidate sequence is assumed to be a true binding site belonging to the set. The efficiency of the method is measured in form of receiver operating characteristic (ROC) curves on different transcription factors from  Saccharomyces cerevisiae  organism. The results are compared with other known motif detection algorithms such as Motif Discovery scan (MDscan) and multiple expectation-maximization (EM) for motif elicitation (MEME)."}]