Abstract
Protein interaction networks are of great importance to understand the biological cellular process. Recent advances in high-throughput detection methods, such as the yeast two hybrid method, have given researchers access to large volumes of PPI network data. However, protein interaction databases published by different research groups use different protein naming systems and have different levels of reliability. In this paper we design ProteinNET, a protein interaction network integration system, to integrate protein interaction databases from different sources and improve the quality of the protein interaction network by using noise reduction techniques. In addition, the proteinNET system provides five methods to visualize the protein interaction network. The ProteinNET system can help researchers explore the protein interaction network of different data sources.
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Cao, T., Wu, X., Hu, X. (2012). ProteinNET: A Protein Interaction Network Integration System. In: Ding, W., Jiang, H., Ali, M., Li, M. (eds) Modern Advances in Intelligent Systems and Tools. Studies in Computational Intelligence, vol 431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30732-4_9
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DOI: https://doi.org/10.1007/978-3-642-30732-4_9
Publisher Name: Springer, Berlin, Heidelberg
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