Systematic assessment of high-throughput experimental data for reliable protein interactions using network topology

Jin Chen, Wynne Hsu, Mong Li Lee, See Kiong Ng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings - 16th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2004
EditorsT.M. Khoshgoftaar
Pages368-372
Number of pages5
DOIs
StatePublished - 2004
EventProceedings - 16th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2004 - Boca Raton, FL, United States
Duration: Nov 15 2004Nov 17 2004

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
ISSN (Print)1082-3409

Conference

ConferenceProceedings - 16th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2004
Country/TerritoryUnited States
CityBoca Raton, FL
Period11/15/0411/17/04

ASJC Scopus subject areas

  • General Engineering

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