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Detecting conserved protein complexes using a dividing-and-matching algorithm and unequally lenient criteria for network comparison

Overview of attention for article published in Algorithms for Molecular Biology, June 2015
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Title
Detecting conserved protein complexes using a dividing-and-matching algorithm and unequally lenient criteria for network comparison
Published in
Algorithms for Molecular Biology, June 2015
DOI 10.1186/s13015-015-0053-5
Pubmed ID
Authors

Wei Peng, Jianxin Wang, Fangxiang Wu, Pan Yi

Abstract

The increase of protein-protein interaction (PPI) data of different species makes it possible to identify common subnetworks (conserved protein complexes) across species via local alignment of their PPI networks, which benefits us to study biological evolution. Local alignment algorithms compare PPI network of different species at both protein sequence and network structure levels. For computational and biological reasons, it is hard to find common subnetworks with strict similar topology from two input PPI networks. Consequently some methods introduce less strict criteria for topological similarity. However those methods fail to consider the differences of the two input networks and adopt equally lenient criteria on them. In this work, a new dividing-and-matching-based method, namely UEDAMAlign is proposed to detect conserved protein complexes. This method firstly uses known protein complexes or computational methods to divide one of the two input PPI networks into subnetworks and then maps the proteins in these subnetworks to the other PPI network to get their homologous proteins. After that, UEDAMAlign conducts unequally lenient criteria on the two input networks to find common connected components from the proteins in the subnetworks and their homologous proteins in the other network. We carry out network alignments between S. cerevisiae and D. melanogaster, H. sapiens and D. melanogaster, respectively. Comparisons are made between other six existing methods and UEDAMAlign. The experimental results show that UEDAMAlign outperforms other existing methods in recovering conserved protein complexes that both match well with known protein complexes and have similar functions.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 13%
Brazil 1 13%
Unknown 6 75%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 38%
Student > Ph. D. Student 2 25%
Student > Doctoral Student 1 13%
Student > Bachelor 1 13%
Researcher 1 13%
Other 0 0%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 38%
Computer Science 2 25%
Biochemistry, Genetics and Molecular Biology 2 25%
Unknown 1 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 July 2015.
All research outputs
#4,421,387
of 5,310,151 outputs
Outputs from Algorithms for Molecular Biology
#95
of 128 outputs
Outputs of similar age
#151,241
of 187,658 outputs
Outputs of similar age from Algorithms for Molecular Biology
#5
of 7 outputs
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