NetCoffee2: A Novel Global Alignment Algorithm for Multiple PPI Networks Based on Graph Feature Vectors

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

5 Scopus citations

Abstract

Network alignment provides a fast and effective framework to automatically identify functionally conserved proteins in a systematic way. However, due to the fast growing biological data, there is an increasing demand for more accurate and efficient tools to deal with multiple PPI networks. Here, we present a novel global alignment algorithm NetCoffee2 to discover functionally conserved proteins. To test the algorithm performance, NetCoffee2 and several existing algorithms were applied on eight real biological datasets. Results show that NetCoffee2 is superior to IsoRankN, NetCoffee and multiMAGNA++ in terms of both coverage and consistency. The binary and source code are freely available at https://github.com/screamer/NetCoffee2.

Original languageEnglish
Title of host publicationIntelligent Computing Theories and Application - 14th International Conference, ICIC 2018, Proceedings
EditorsKang-Hyun Jo, De-Shuang Huang, Xiao-Long Zhang
PublisherSpringer Verlag
Pages241-246
Number of pages6
ISBN (Print)9783319959320
DOIs
StatePublished - 2018
Event14th International Conference on Intelligent Computing, ICIC 2018 - Wuhan, China
Duration: 15 Aug 201818 Aug 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10955 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Intelligent Computing, ICIC 2018
Country/TerritoryChina
CityWuhan
Period15/08/1818/08/18

Keywords

  • Functionally conserved proteins
  • PPI network alignment
  • Simulated annealing

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