Title :
Systematic assessment of high-throughput experimental data for reliable protein interactions using network topology
Author :
Chen, Jin ; Hsu, Wynne ; Lee, Mong Li ; Ng, See-Kiong
Author_Institution :
Sch. of Comput., Nat. Univ. of Singapore, Singapore
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.
Keywords :
data mining; heuristic programming; medical information systems; proteins; very large databases; candidate protein interaction; heuristic algorithm; network topology; protein interaction network; very large database; Algorithm design and analysis; Biology computing; Computer networks; Heuristic algorithms; Maintenance; Network topology; Performance evaluation; Protein engineering; Semiconductor device measurement; Throughput;
Conference_Titel :
Tools with Artificial Intelligence, 2004. ICTAI 2004. 16th IEEE International Conference on
Print_ISBN :
0-7695-2236-X
DOI :
10.1109/ICTAI.2004.112