CAMWI: Detecting protein complexes using weighted clustering coefficient and weighted density |
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Institution: | 1. Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA;2. Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University, New Haven, CT, USA;3. Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA;4. Department of Biomedical Engineering, Yale University, New Haven, CT, USA;5. Department of Neurobiology, Yale University, New Haven, CT, USA;6. The John B. Pierce Laboratory, New Haven, CT, USA |
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Abstract: | Detection of protein complexes is very important to understand the principles of cellular organization and function. Recently, large protein–protein interactions (PPIs) networks have become available using high-throughput experimental techniques. These networks make it possible to develop computational methods for protein complex detection. Most of the current methods rely on the assumption that protein complex as a module has dense structure. However complexes have core-attachment structure and proteins in a complex core share a high degree of functional similarity, so it expects that a core has high weighted density. In this paper we present a Core-Attachment based method for protein complex detection from Weighted PPI Interactions using clustering coefficient and weighted density. Experimental results show that the proposed method, CAMWI improves the accuracy of protein complex detection. |
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Keywords: | Protein complex Core-attachment structure Clustering coefficient Graph weighted density |
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