A robust network alignment algorithm for detecting evolutionarily conserved networks and protein complexes across species

Yu Chun Lin; Hsiang Yuan Yeh; Cheng Yu Yeh; Von Wun Soo

A robust network alignment algorithm for detecting evolutionarily conserved networks and protein complexes across species

Yu Chun Lin^*, Hsiang Yuan Yeh, Cheng Yu Yeh, Von Wun Soo

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Due to the complexity of the biological networks, it is difficult to extract the conserved modules across species with graphical representation. One of the arising challenges is to compare different networks in order to analyze and discover common sub-networks, especially cliqued structure of protein complexes that may share similar biological functions. We combine sequence alignment and ontology-based semantic similarity score to cluster potential orthologous proteins and use depth-first search for network comparison to discover the conserved networks and protein complexes across species. This method allows the biological evolutions such as duplication and divergence to be tolerated in the network alignment process under a user specified value ε. We apply network alignment for two large protein-protein interactions (Saccharomyces cerevisiae and Caenorhabditis elegans) as our test data. We detect a large number of conserved networks and true complexes that match in the yeast MIPS database.

Original language	English
Title of host publication	Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008
Pages	1005-1011
Number of pages	7
State	Published - 2008
Externally published	Yes
Event	2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008 - Las Vegas, NV, United States Duration: 14 07 2008 → 17 07 2008

Publication series

Name	Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008

Conference

Conference	2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008
Country/Territory	United States
City	Las Vegas, NV
Period	14/07/08 → 17/07/08

Keywords

Across species
Networks comparison
Ontology-based semantic similarity
Protein complexes

Cite this

Lin, Y. C., Yeh, H. Y., Yeh, C. Y., & Soo, V. W. (2008). A robust network alignment algorithm for detecting evolutionarily conserved networks and protein complexes across species. In Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008 (pp. 1005-1011). (Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008).

Lin, Yu Chun ; Yeh, Hsiang Yuan ; Yeh, Cheng Yu et al. / A robust network alignment algorithm for detecting evolutionarily conserved networks and protein complexes across species. Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008. 2008. pp. 1005-1011 (Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008).

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title = "A robust network alignment algorithm for detecting evolutionarily conserved networks and protein complexes across species",

abstract = "Due to the complexity of the biological networks, it is difficult to extract the conserved modules across species with graphical representation. One of the arising challenges is to compare different networks in order to analyze and discover common sub-networks, especially cliqued structure of protein complexes that may share similar biological functions. We combine sequence alignment and ontology-based semantic similarity score to cluster potential orthologous proteins and use depth-first search for network comparison to discover the conserved networks and protein complexes across species. This method allows the biological evolutions such as duplication and divergence to be tolerated in the network alignment process under a user specified value ε. We apply network alignment for two large protein-protein interactions (Saccharomyces cerevisiae and Caenorhabditis elegans) as our test data. We detect a large number of conserved networks and true complexes that match in the yeast MIPS database.",

keywords = "Across species, Networks comparison, Ontology-based semantic similarity, Protein complexes",

author = "Lin, {Yu Chun} and Yeh, {Hsiang Yuan} and Yeh, {Cheng Yu} and Soo, {Von Wun}",

year = "2008",

language = "英语",

isbn = "1601320558",

series = "Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008",

pages = "1005--1011",

booktitle = "Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008",

note = "2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008 ; Conference date: 14-07-2008 Through 17-07-2008",

}

Lin, YC, Yeh, HY, Yeh, CY & Soo, VW 2008, A robust network alignment algorithm for detecting evolutionarily conserved networks and protein complexes across species. in Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008. Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008, pp. 1005-1011, 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008, Las Vegas, NV, United States, 14/07/08.

A robust network alignment algorithm for detecting evolutionarily conserved networks and protein complexes across species. / Lin, Yu Chun; Yeh, Hsiang Yuan; Yeh, Cheng Yu et al.
Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008. 2008. p. 1005-1011 (Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A robust network alignment algorithm for detecting evolutionarily conserved networks and protein complexes across species

AU - Lin, Yu Chun

AU - Yeh, Hsiang Yuan

AU - Yeh, Cheng Yu

AU - Soo, Von Wun

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N2 - Due to the complexity of the biological networks, it is difficult to extract the conserved modules across species with graphical representation. One of the arising challenges is to compare different networks in order to analyze and discover common sub-networks, especially cliqued structure of protein complexes that may share similar biological functions. We combine sequence alignment and ontology-based semantic similarity score to cluster potential orthologous proteins and use depth-first search for network comparison to discover the conserved networks and protein complexes across species. This method allows the biological evolutions such as duplication and divergence to be tolerated in the network alignment process under a user specified value ε. We apply network alignment for two large protein-protein interactions (Saccharomyces cerevisiae and Caenorhabditis elegans) as our test data. We detect a large number of conserved networks and true complexes that match in the yeast MIPS database.

AB - Due to the complexity of the biological networks, it is difficult to extract the conserved modules across species with graphical representation. One of the arising challenges is to compare different networks in order to analyze and discover common sub-networks, especially cliqued structure of protein complexes that may share similar biological functions. We combine sequence alignment and ontology-based semantic similarity score to cluster potential orthologous proteins and use depth-first search for network comparison to discover the conserved networks and protein complexes across species. This method allows the biological evolutions such as duplication and divergence to be tolerated in the network alignment process under a user specified value ε. We apply network alignment for two large protein-protein interactions (Saccharomyces cerevisiae and Caenorhabditis elegans) as our test data. We detect a large number of conserved networks and true complexes that match in the yeast MIPS database.

KW - Across species

KW - Networks comparison

KW - Ontology-based semantic similarity

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BT - Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008

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Lin YC, Yeh HY, Yeh CY, Soo VW. A robust network alignment algorithm for detecting evolutionarily conserved networks and protein complexes across species. In Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008. 2008. p. 1005-1011. (Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008).

A robust network alignment algorithm for detecting evolutionarily conserved networks and protein complexes across species

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Keywords

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