Exploiting locational and topological overlap model to identify modules in protein interaction networks
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Title
Exploiting locational and topological overlap model to identify modules in protein interaction networks
Authors
Keywords
Protein interaction network, Network clustering, Subcellular localization, Topological overlap, Functional module
Journal
BMC BIOINFORMATICS
Volume 20, Issue 1, Pages -
Publisher
Springer Nature
Online
2019-01-14
DOI
10.1186/s12859-019-2598-7
References
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Related references
Note: Only part of the references are listed.- SMILE: a novel procedure for subcellular module identification with localisation expansion
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- (2017) Lixin Cheng et al. JOURNAL OF PROTEOME RESEARCH
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- (2015) Chern Han Yong et al. Biology Direct
- A dual role of p53 in the control of autophagy
- (2014) Ezgi Tasdemir et al. Autophagy
- ComPPI: a cellular compartment-specific database for protein–protein interaction network analysis
- (2014) Daniel V. Veres et al. NUCLEIC ACIDS RESEARCH
- The BioGRID interaction database: 2015 update
- (2014) Andrew Chatr-aryamontri et al. NUCLEIC ACIDS RESEARCH
- RAID: a comprehensive resource for human RNA-associated (RNA-RNA/RNA-protein) interaction
- (2014) X. Zhang et al. RNA
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- (2013) Yifei Li et al. Autophagy
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- Protein localization as a principal feature of the etiology and comorbidity of genetic diseases
- (2011) S. Park et al. Molecular Systems Biology
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- (2011) Q. Liao et al. NUCLEIC ACIDS RESEARCH
- Discovering approximate-associated sequence patterns for protein–DNA interactions
- (2010) Tak-Ming Chan et al. BIOINFORMATICS
- Recent advances in clustering methods for protein interaction networks
- (2010) Jianxin Wang et al. BMC GENOMICS
- MIPS: curated databases and comprehensive secondary data resources in 2010
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- A human functional protein interaction network and its application to cancer data analysis
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- Human Cancer Protein-Protein Interaction Network: A Structural Perspective
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- High-Quality Binary Protein Interaction Map of the Yeast Interactome Network
- (2008) H. Yu et al. SCIENCE
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