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IPCA specifications

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Unique identifier OMICS_11241
Name IPCA
Software type Application/Script
Interface Command line interface
Restrictions to use Academic or non-commercial use
Operating system Unix/Linux, Windows
Programming languages C++
Computer skills Advanced
Stability No
Maintained No

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Publication for IPCA

IPCA citations

 (20)
library_books

Identification of protein complexes from multi relationship protein interaction networks

2016
Hum Genomics
PMCID: 4965713
PMID: 27461193
DOI: 10.1186/s40246-016-0069-z

[…] in clustering algorithm) [], hc-pin (hierarchical clustering based on protein-protein interaction network) [], ipc-mce (identifying protein complexes based on maximal clique extension) [], and ipca (identification of protein complexes algorithm) []. nepusz et al. [] proposed an algorithm to find overlapping protein complexes from ppi networks, named clusterone (clustering with overlapping […]

library_books

A density based clustering approach for identifying overlapping protein complexes with functional preferences

2015
BMC Bioinformatics
PMCID: 4445992
PMID: 26013799
DOI: 10.1186/s12859-015-0583-3

[…] beings., for the purpose of performance evaluation, we compared dcafp with the state-of-the-art approaches including gmftp [], pcia [], mcl [], mcode [], rnsc [], cfinder [], cmc [], coach [] and ipca []. briefly speaking, for identifying protein complexes, gmftp and pcia considered the functional information of proteins and the graph topology of ppi network simultaneously […]

library_books

Clustering PPI data by combining FA and SHC method

2015
BMC Genomics
PMCID: 4331806
PMID: 25707632
DOI: 10.1186/1471-2164-16-S3-S3

[…] expression data and detect protein complexes basing on uncertain graph model [,],there are many new algorithms also, such as ovrlp, pe-wcc, uvcluster, ap, gfa, admsc, sci-bn, core, fag-ec, hc-pin, ipca, cp-dr, lf-pin, abc algorithm [-] and so on., synchronization is a natural phenomenon ranging from the metabolism in the cell to social behavior in groups of individuals regulating a large […]

library_books

Discovery of small protein complexes from PPI networks with size specific supervised weighting

2014
BMC Syst Biol
PMCID: 4305982
PMID: 25559663
DOI: 10.1186/1752-0509-8-S5-S3

[…] small complex prediction using our weighting approach (sss) versus ppi reliability (ppirel), and using our complex extraction algorithm (extract) versus other clustering algorithms (cmc, clusterone, ipca, mcl, rnsc, ppsampler2). figure shows the performance of prediction of yeast small complexes, in terms of precision-recall auc. our 2-stage approach (sss + extract) outperforms […]

library_books

Prediction of disease related genes based on weighted tissue specific networks by using DNA methylation

2014
BMC Med Genomics
PMCID: 4243158
PMID: 25350763
DOI: 10.1186/1755-8794-7-S2-S4

[…] analysis method to predict human disease-related gene clusters based on the network. in addition, some typical graph partitioning methods and clustering approaches, such as gs[], mcl [], vi-cut [], ipca [], mscf [], hc-pin[], rw[], and their improved algorithms, can also be used to discover candidate disease-related genes., although great progresses have been made on the network-based methods, […]

library_books

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

2014
Biomed Res Int
PMCID: 4052612
PMID: 24963481
DOI: 10.1155/2014/375262

[…] the combination of density and peripheral proteins to mine densely connected subgraphs. by modifying the dpclus algorithm based on new topological structures, our group proposed a new method named ipca [] to identify dense subgraphs as protein complexes. ding et al. [] detected dense subgraphs by using minimum vertex cuts on ppi network. chen et al. [] introduced a novel method using cliques […]


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IPCA institution(s)
School of Information Science and Engineering, Central South University, Changsha, Hunan, China; Department of Computer Science, Texas A&M University, College Station, TX, USA
IPCA funding source(s)
This research is supported in part by the National Science Foundation of China under Grant No. 60433020.

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