Global voting model for protein function prediction from protein-protein interaction networks

Yi Fang, Mengtian Sun, Guoxian Dai, Karthik Ramani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It is known that the observed PPI network is incomplete with low coverage and high rate of false positives and false negatives. Computational approach is likely to be overwhelmed by the high level of noises and incompleteness if relying on local topological information.We propose a global voting (GV) model to predict protein function by exploiting the entire topology of the network. GV consistently assigns function to unannotated proteins through a global voting procedure in which all of the annotated proteins participate. It assigns a list of function candidates to a target protein with each attached a probability score. The probability indicates the confidence level of the potential function assignment. We apply GV model to a yeast PPI network and test the robustness of the model against noise by random insertion and deletion of true PPIs. The results demonstrate that GV model can robustly infer the function of the proteins.

Original languageEnglish (US)
Title of host publicationIntelligent Computing in Bioinformatics - 10th International Conference, ICIC 2014, Proceedings
PublisherSpringer-Verlag
Pages466-477
Number of pages12
ISBN (Print)9783319093291
DOIs
StatePublished - Jan 1 2014
Event10th International Conference on Intelligent Computing, ICIC 2014 - Taiyuan, China
Duration: Aug 3 2014Aug 6 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8590 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other10th International Conference on Intelligent Computing, ICIC 2014
CountryChina
CityTaiyuan
Period8/3/148/6/14

Fingerprint

Protein Interaction Networks
Protein-protein Interaction
Voting
Proteins
Protein
Prediction
Assign
Model
Incompleteness
Confidence Level
Potential Function
False Positive
Yeast
Deletion
Insertion
Coverage
Assignment
Likely
Topology
Entire

Keywords

  • Diffusion Geometry
  • PPI Network
  • protein function prediction

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Fang, Y., Sun, M., Dai, G., & Ramani, K. (2014). Global voting model for protein function prediction from protein-protein interaction networks. In Intelligent Computing in Bioinformatics - 10th International Conference, ICIC 2014, Proceedings (pp. 466-477). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8590 LNBI). Springer-Verlag. https://doi.org/10.1007/978-3-319-09330-7_54

Global voting model for protein function prediction from protein-protein interaction networks. / Fang, Yi; Sun, Mengtian; Dai, Guoxian; Ramani, Karthik.

Intelligent Computing in Bioinformatics - 10th International Conference, ICIC 2014, Proceedings. Springer-Verlag, 2014. p. 466-477 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8590 LNBI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Fang, Y, Sun, M, Dai, G & Ramani, K 2014, Global voting model for protein function prediction from protein-protein interaction networks. in Intelligent Computing in Bioinformatics - 10th International Conference, ICIC 2014, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8590 LNBI, Springer-Verlag, pp. 466-477, 10th International Conference on Intelligent Computing, ICIC 2014, Taiyuan, China, 8/3/14. https://doi.org/10.1007/978-3-319-09330-7_54
Fang Y, Sun M, Dai G, Ramani K. Global voting model for protein function prediction from protein-protein interaction networks. In Intelligent Computing in Bioinformatics - 10th International Conference, ICIC 2014, Proceedings. Springer-Verlag. 2014. p. 466-477. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-09330-7_54
Fang, Yi ; Sun, Mengtian ; Dai, Guoxian ; Ramani, Karthik. / Global voting model for protein function prediction from protein-protein interaction networks. Intelligent Computing in Bioinformatics - 10th International Conference, ICIC 2014, Proceedings. Springer-Verlag, 2014. pp. 466-477 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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