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|Title:||Systematic assessment of high-throughput experimental data for reliable protein interactions using network topology|
|Citation:||Chen, J.,Hsu, W.,Lee, M.L.,Ng, S.-K. (2004). Systematic assessment of high-throughput experimental data for reliable protein interactions using network topology. Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI : 368-372. ScholarBank@NUS Repository. https://doi.org/10.1109/ICTAI.2004.112|
|Abstract:||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 the protein 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 as 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. © 2004 IEEE.|
|Source Title:||Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI|
|Appears in Collections:||Staff Publications|
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