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Systematic Assessment of High-Throughput Experimental Data for Reliable Protein Interactions Using Network Topology
Boca Raton, Florida November 15-November 17
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICTAI.2004.11216th IEEE International Conference on ...
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Jin Chen, National University of Singapore
Wynne Hsu, National University of Singapore
Mong Li Lee, National University of Singapore
See-Kiong Ng, Institute for Inforcomm Research
Current protein interaction detection via high-throughput experimental methods such as yeast-two-hybrid has been reported to be highly erroneous. This work introduces a novel measure called IRAP for assessing the reliability of protein interaction based on the underlying topology of theprotein interaction network. A candidate protein interaction is considered to be reliable if it is involved in a closed loop in which the alternative path of interactions between the two interacting proteins is strong. We design an algorithm to compute the IRAP value for each interaction in a protein interaction network. Validation of IRAP æ a measure for assessing the reliability of protein-protein interactions from conventional high-throughput experiments is performed. We devise a heuristic algorithm to compute IRAP that is able to achieve a 40% speedup in runtime while maintaining a 95% accuracy.
Citation:
Jin Chen, Wynne Hsu, Mong Li Lee, See-Kiong Ng, "Systematic Assessment of High-Throughput Experimental Data for Reliable Protein Interactions Using Network Topology," ictai, pp.368-372, 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'04), 2004
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