16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'04)
Systematic Assessment of High-Throughput Experimental Data for Reliable Protein Interactions Using Network Topology
Boca Raton, Florida
November 15-November 17
ISBN: 0-7695-2236-X
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