Profiling of Disease-Associated Proteins Neighborhood Networks
| Autor: | Sourav Dutta, Sheheeda Manakkadu, Sam R. Thangiah |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Connected component Profiling (computer programming) Computer science Social connectedness 0206 medical engineering 02 engineering and technology Disease Computational biology 03 medical and health sciences 030104 developmental biology Reachability Metric (mathematics) 020602 bioinformatics |
| Zdroj: | BigDataSE |
| DOI: | 10.1109/bigdatase50710.2020.00009 |
| Popis: | Discovering disease-associated proteins in the human Protein-Protein Interaction (PPI) network is an important problem. Several algorithms have been proposed to discover these proteins from an initial set of known disease-associated proteins. A majority of these algorithms depend on the connectedness of disease-associated proteins in the PPI network. In this paper, We performed an experimental study to understand the interaction between disease-associated proteins and their neighbors. We observe that most disease-associated proteins have common neighbors in the PPI network. We performed comparative analysis on the interaction of disease proteins in disease-associated proteins neighborhood networks and networks consisting of only disease proteins. Our experimental results show that for all disease that we considered in this study, have a higher number of disease proteins in the largest connected component in the disease-associated proteins neighborhood network. We develop a score metric to capture the reachability of disease-associated proteins via common neighborhood proteins that not necessarily associated with a disease. We observe that a high number of disease proteins are part of the largest connected component in the neighborhood network with fewer disease proteins are disconnected forming separately connected components. we also develop a reachability metric to profile diseases based on the connectedness of associated proteins based on the number of components and the density of disease proteins in a disease-associated protein neighborhood network. |
| Databáze: | OpenAIRE |
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