GenRev: Exploring functional relevance of genes in molecular networks

Siyuan Zheng; Zhongming Zhao

doi:10.1016/j.ygeno.2011.12.005

GenRev: Exploring functional relevance of genes in molecular networks

Siyuan Zheng, Zhongming Zhao

Research output: Contribution to journal › Article › peer-review

41 Scopus citations

Abstract

We introduce GenRev, a network-based software package developed to explore the functional relevance of genes generated as an intermediate result from numerous high-throughput technologies. GenRev searches for optimal intermediate nodes (genes) for the connection of input nodes via several algorithms, including the Klein-Ravi algorithm, the limited kWalks algorithm and a heuristic local search algorithm. Gene ranking and graph clustering analyses are integrated into the package. GenRev has the following features. (1) It provides users with great flexibility to define their own networks. (2) Users are allowed to define each gene's importance in a subnetwork search by setting its score. (3) It is standalone and platform independent. (4) It provides an optimization in subnetwork search, which dramatically reduces the running time. GenRev is particularly designed for general use so that users have the flexibility to choose a reference network and define the score of genes. GenRev is freely available at http://bioinfo.mc.vanderbilt.edu/GenRev.html.

Original language	English (US)
Pages (from-to)	183-188
Number of pages	6
Journal	Genomics
Volume	99
Issue number	3
DOIs	https://doi.org/10.1016/j.ygeno.2011.12.005
State	Published - Mar 2012
Externally published	Yes

Keywords

Disease genes
Gene ranking
Klein-Ravi algorithm
Limited kWalks algorithm
Network
Subnetwork

ASJC Scopus subject areas

Genetics

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10.1016/j.ygeno.2011.12.005

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title = "GenRev: Exploring functional relevance of genes in molecular networks",

abstract = "We introduce GenRev, a network-based software package developed to explore the functional relevance of genes generated as an intermediate result from numerous high-throughput technologies. GenRev searches for optimal intermediate nodes (genes) for the connection of input nodes via several algorithms, including the Klein-Ravi algorithm, the limited kWalks algorithm and a heuristic local search algorithm. Gene ranking and graph clustering analyses are integrated into the package. GenRev has the following features. (1) It provides users with great flexibility to define their own networks. (2) Users are allowed to define each gene's importance in a subnetwork search by setting its score. (3) It is standalone and platform independent. (4) It provides an optimization in subnetwork search, which dramatically reduces the running time. GenRev is particularly designed for general use so that users have the flexibility to choose a reference network and define the score of genes. GenRev is freely available at http://bioinfo.mc.vanderbilt.edu/GenRev.html.",

keywords = "Disease genes, Gene ranking, Klein-Ravi algorithm, Limited kWalks algorithm, Network, Subnetwork",

author = "Siyuan Zheng and Zhongming Zhao",

note = "Funding Information: This project was partially supported by the NIH grants ( R03DE022093 ) and 2009 NARSAD Maltz Investigator Award (to Z.Z.). We thank the anonymous reviewers for their valuable comments. We thank Dr. Peilin Jia for her valuable contribution in the revision of the manuscript, Dr. Pierre Dupont for his kind help in the implementation of the limited k-walk algorithm, and Ms. Rebecca H. Posey for critically reading and improving the manuscript. We also thank the members of the Bioinformatics and Systems Medicine Laboratory in Vanderbilt University for their useful discussion and suggestions.",

year = "2012",

month = mar,

doi = "10.1016/j.ygeno.2011.12.005",

language = "English (US)",

volume = "99",

pages = "183--188",

journal = "Genomics",

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N1 - Funding Information: This project was partially supported by the NIH grants ( R03DE022093 ) and 2009 NARSAD Maltz Investigator Award (to Z.Z.). We thank the anonymous reviewers for their valuable comments. We thank Dr. Peilin Jia for her valuable contribution in the revision of the manuscript, Dr. Pierre Dupont for his kind help in the implementation of the limited k-walk algorithm, and Ms. Rebecca H. Posey for critically reading and improving the manuscript. We also thank the members of the Bioinformatics and Systems Medicine Laboratory in Vanderbilt University for their useful discussion and suggestions.

PY - 2012/3

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N2 - We introduce GenRev, a network-based software package developed to explore the functional relevance of genes generated as an intermediate result from numerous high-throughput technologies. GenRev searches for optimal intermediate nodes (genes) for the connection of input nodes via several algorithms, including the Klein-Ravi algorithm, the limited kWalks algorithm and a heuristic local search algorithm. Gene ranking and graph clustering analyses are integrated into the package. GenRev has the following features. (1) It provides users with great flexibility to define their own networks. (2) Users are allowed to define each gene's importance in a subnetwork search by setting its score. (3) It is standalone and platform independent. (4) It provides an optimization in subnetwork search, which dramatically reduces the running time. GenRev is particularly designed for general use so that users have the flexibility to choose a reference network and define the score of genes. GenRev is freely available at http://bioinfo.mc.vanderbilt.edu/GenRev.html.

AB - We introduce GenRev, a network-based software package developed to explore the functional relevance of genes generated as an intermediate result from numerous high-throughput technologies. GenRev searches for optimal intermediate nodes (genes) for the connection of input nodes via several algorithms, including the Klein-Ravi algorithm, the limited kWalks algorithm and a heuristic local search algorithm. Gene ranking and graph clustering analyses are integrated into the package. GenRev has the following features. (1) It provides users with great flexibility to define their own networks. (2) Users are allowed to define each gene's importance in a subnetwork search by setting its score. (3) It is standalone and platform independent. (4) It provides an optimization in subnetwork search, which dramatically reduces the running time. GenRev is particularly designed for general use so that users have the flexibility to choose a reference network and define the score of genes. GenRev is freely available at http://bioinfo.mc.vanderbilt.edu/GenRev.html.

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KW - Limited kWalks algorithm

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KW - Subnetwork

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GenRev: Exploring functional relevance of genes in molecular networks

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Keywords

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