Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivation: Several methods have recently been developed to analyse large-scale sets of physical interactions beten proteins in terms of physical contacts beten the constituent domains, often with a view to predicting new pairwise interactions. Our aim is to combine genomic interaction data, in which domain--domain contacts are not explicitly reported, with the domain-level structure of individual proteins, in order to learn about the structure of interacting protein pairs. Our approach is driven by the need to assess the evidence for physical contacts beten domains in a statistically rigorous way.#R##N##R##N#Results:  develop a statistical approach that assigns p-values to pairs of domain superfamilies, measuring the strength of evidence within a set of protein interactions that domains from these superfamilies form contacts. A set of p-values is calculated for SCOP superfamily pairs, based on a pooled data set of interactions from yeast. These p-values can be used to predict which domains come into contact in an interacting protein pair. This predictive scheme is tested against protein complexes in the Protein Quaternary Structure (PQS) database, and is used to predict domain--domain contacts within 705 interacting protein pairs taken from our pooled data set.#R##N##R##N#Contact: thomas.nye@mrc-bsu.cam.ac.uk
['Tom M. W. Nye', 'Carlo Berzuini', 'Walter R. Gilks', 'Madan Mohan Babu', 'Sarah A. Teichmann']
I am writing a research paper on a idea Statistical analysis of domains in interacting protein pairs
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