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An Algorithm for Finding Functional Modules and Protein Complexes in Protein-Protein Interaction Networks

Guangyu Cui, Yu Chen, De-Shuang Huang, Kyungsook Han
2008 Journal of Biomedicine and Biotechnology  
We have developed an efficient algorithm and program for finding cliques and near-cliques in a protein-protein interaction network.  ...  Analysis of the interaction network of yeast proteins using the algorithm demonstrates that 59% of the near-cliques identified by our algorithm have at least one function shared by all the proteins within  ...  The primary focus of this study is to find functional groups by identifying cliques and near-cliques in protein interaction networks. This study attempts to answer two ques-tions as follows.  ... 
doi:10.1155/2008/860270 pmid:18385821 pmcid:PMC2278021 fatcat:nhjyabfecfgrlmgx735fyqr64i

NCMine: Core-peripheral based functional module detection using near-clique mining

Shu Tadaka, Kengo Kinoshita
2016 Bioinformatics  
The detection of functional modules in PPI networks is often performed by identifying internally densely connected subnetworks, and often produces modules with "core" and "peripheral" proteins.  ...  Motivation: The identification of functional modules from protein-protein interaction (PPI) networks is an important step toward understanding the biological features of PPI networks.  ...  Funding This research was partially supported by the Platform Project for Supporting in Drug Discovery and Life Science Research (Platform for Drug Discovery, Informatics, and Structural Life Science)  ... 
doi:10.1093/bioinformatics/btw488 pmid:27466623 pmcid:PMC5181566 fatcat:kpkhchfrlrcgtc4hes6isq63h4

Modular clustering of protein-protein interaction networks

Nassim Sohaee, Christian V. Forst
2010 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology  
Dense subgraphs of Protein-Protein Interaction (PPI) graphs are assumed to be potential functional modules and play an important role in inferring the functional behavior of proteins.  ...  The method is based on finding bounded diameter subgraphs around a seed node. The algorithm has the advantage over other graph clustering methods of being very simple and efficient.  ...  Results and Discussions Identifying hidden topological structures of protein interaction networks often unveil biologically relevant functional groups and structural complexes.  ... 
doi:10.1109/cibcb.2010.5510590 dblp:conf/cibcb/SohaeeF10 fatcat:ruc2v7mezbao3hd4qmqn7pc6ga

Detecting highly overlapping community structure by greedy clique expansion [article]

Conrad Lee, Fergal Reid, Aaron McDaid, Neil Hurley (Clique Research Cluster, University College Dublin, Ireland)
2010 arXiv   pre-print
Furthermore, when put to the task of identifying functional modules in protein interaction data, and college dorm assignments in Facebook friendship data, we find that GCE performs competitively.  ...  The algorithm identifies distinct cliques as seeds and expands these seeds by greedily optimizing a local fitness function.  ...  Protein-protein interactions and protein complexes. Protein complexes tend to correspond to groups of proteins with many interactions, and can thus be detected by CAAs.  ... 
arXiv:1002.1827v2 fatcat:l277qlm5o5dkxa5zss63kajdu4

A Coevolutionary Residue Network at the Site of a Functionally Important Conformational Change in a Phosphohexomutase Enzyme Family

Yingying Lee, Jacob Mick, Cristina Furdui, Lesa J. Beamer, Ashley M. Buckle
2012 PLoS ONE  
The results of these studies are interpreted in the context of structural and functional data on PMM/PGM.  ...  Mutual information and graph theory were utilized to identify a network of highly connected residues with high significance.  ...  Acknowledgments We thank MU Bioinformatics Core for computational resources and Ritcha Mehra-Chaudhary of the MU Structural Biology Core for technical assistance and helpful discussions.  ... 
doi:10.1371/journal.pone.0038114 pmid:22685552 pmcid:PMC3369874 fatcat:o7n763ysd5gw5nv356ndmavs6i

Identification of dysregulated modules based on network entropy in type 1 diabetes

Yan Zheng, Liwei Liu, Jifeng Ye
2018 Experimental and Therapeutic Medicine  
By integrating gene expression data and protein-protein interactions (PPI) data, 48,778 new networks were obtained, including 7,953 genes. After simplifying networks, we obtained 24 target networks.  ...  By ranking networks with P-values, two modules with P<0.05 were identified, including the genes, CCNB1, CDC45, GINS2, NDC80, FBXO5, NCAPG and DLGAP5. Module 2 was part of module 1.  ...  By combining gene expression data and protein-protein interactions (PPI) data, we constructed target networks.  ... 
doi:10.3892/etm.2018.5803 pmid:29545837 pmcid:PMC5841047 fatcat:m7c645p46nfntgeccjybzkfe3e

Functional networks of the human bromodomain-containing proteins [article]

Cong Gao, Karen C Glass, Seth E Frietze
2022 bioRxiv   pre-print
We identified dense subgraphs formed by BRD proteins and find that different BRD proteins share topological similarity and functional associations.  ...  Conclusions: In our network analysis we confirmed that BRD proteins are conserved central nodes in the human PPI network and function as scaffolds to form distinctive functional clusters.  ...  To reduce computation time, we used the according function in igraph package (Csardi and Nepusz 2006) (limiting size >=3) and identify cliques of BRD proteins in BRD PPIN only formed by BRD proteins.  ... 
doi:10.1101/2022.02.21.481364 fatcat:ocvzsk46vre4rknkoql4e2tnsq

Systematic Tracking of Disrupted Modules Identifies Altered Pathways Associated with Congenital Heart Defects in Down Syndrome

Denghong Chen, Zhenhua Zhang, Yuxiu Meng
2015 Medical Science Monitor  
This work aimed to identify altered pathways in congenital heart defects (CHD) in Down syndrome (DS) by systematically tracking the dysregulated modules of reweighted protein-protein interaction (PPI)  ...  Then, modules in the PPI network were explored by clique-merging algorithm; altered modules were identified via maximum weight bipartite matching and ranked in non-increasing order.  ...  Acknowledgments We thank members of the research group of Jining No.  ... 
pmid:26524729 pmcid:PMC4635630 fatcat:j6rcifkbpbh7dpnx2m56jbu6gm

Unraveling Protein Networks with Power Graph Analysis

Loïc Royer, Matthias Reimann, Bill Andreopoulos, Michael Schroeder, Johannes Berg
2008 PLoS Computational Biology  
Power Graphs compress up to 85% of the edges in protein interaction networks and are applicable to all types of networks such as protein interactions, regulatory networks, or homology networks.  ...  Experimental networks are more compressible than rewired ones of same degree distribution, indicating that experimental networks are rich in cliques and bicliques.  ...  Thanks also go to Andreas Beyer for critique and for suggesting the analysis of his transcription factor to target genes network [65] .  ... 
doi:10.1371/journal.pcbi.1000108 pmid:18617988 pmcid:PMC2424176 fatcat:eaes73hv2vbnnejquzy5pvtoxa

Predicting Meiotic Pathways in Human Fetal Oogenesis1

Ping Zheng, Michael D. Griswold, Terry J. Hassold, Patricia A. Hunt, Christopher L. Small, Ping Ye
2010 Biology of Reproduction  
This global functional network provides a much-needed framework for exploring gene functions and pathway components in early human female meiosis that are difficult to tackle by traditional in vivo mammalian  ...  In this study, we developed the first functional gene network for the human fetal ovary, HFOnet, by probabilistically integrating multiple genomic features using a naïve Bayesian model.  ...  RESULTS A Probabilistic Functional Network for the Human Fetal Ovary Naïve Bayesian networks have been used to identify protein-protein interactions and gene functional associations in yeast, mice, and  ... 
doi:10.1095/biolreprod.109.079590 pmid:19846598 fatcat:ba7uxgpgzva3xijr7vmadq5fyy

Mining Functional Modules in Genetic Networks with Decomposable Graphical Models

Mathäus Dejori, Anton Schwaighofer, Volker Tresp, Martin Stetter
2004 Omics  
We show that the method successfully groups members of known functional modules to cliques.  ...  Our method allows the evaluation of the importance of genes for global cellular functions based on both link count and the clique membership count. 3  ...  Dejori and A. Schwaighofer gratefully acknowledge support through an Ernst v Siemens scholarship.  ... 
doi:10.1089/1536231041388375 pmid:15268775 fatcat:5m2q7hf32zbyrpdnnol7ejef6q

Elucidation of the conformational free energy landscape in H.pylori LuxS and its implications to catalysis

Moitrayee Bhattacharyya, Saraswathi Vishveshwara
2010 BMC Structural Biology  
These investigations have enabled us to probe the free energy landscape and identify the corresponding conformations in terms of network parameters.  ...  The methodology outlined here is highly generalized to illuminate the linkage between structure and function in any protein of known structure.  ...  Authors' contributions MB and SV designed the study, MB performed the calculations, MB and SV analyzed the data, MB and SV drafted the manuscript. All authors read and approved the final manuscript.  ... 
doi:10.1186/1472-6807-10-27 pmid:20704697 pmcid:PMC2929236 fatcat:k6ztmdvhend25nnmwggfukq7bm

Functional networks of the human bromodomain-containing proteins

Cong Gao, Karen C. Glass, Seth Frietze
2022 Frontiers in Bioinformatics  
We identified dense subgraphs formed by BRD proteins and find that different BRD proteins share topological similarity and functional associations.  ...  We explored the functional relationships through clustering and Hallmark pathway gene set enrichment analysis and identify potential biological roles for different BRD proteins.Conclusion: In our network  ...  To reduce computation time, we used the according function in igraph package (Csardi and Nepusz, 2006) (limiting size≥3) and identify cliques of BRD proteins in BRD PPIN only formed by BRD proteins.  ... 
doi:10.3389/fbinf.2022.835892 fatcat:rpjs4njufra4tch4oc7cjd7tpu

PPI network analyses of human WD40 protein family systematically reveal their tendency to assemble complexes and facilitate the complex predictions

Xu-Dong Zou, Ke An, Yun-Dong Wu, Zhi-Qiang Ye
2018 BMC Systems Biology  
may serve as hubs in the protein-protein interaction (PPI) network.  ...  WD40 repeat proteins constitute one of the largest families in eukaryotes, and widely participate in various fundamental cellular processes by interacting with other molecules.  ...  Availability of data and materials The data sets in this study are available as Additional files.  ... 
doi:10.1186/s12918-018-0567-9 pmid:29745845 pmcid:PMC5998875 fatcat:m4yspnwgm5e6tiu56ulfurh36q

Protein Function Prediction Using Protein–Protein Interaction Networks [chapter]

Hon Nian Chua, Guimei Liu, Limsoon Wong
2011 Protein Function Prediction for Omics Era  
Proteins perform biological functions by participating in a large number of interactions, ranging from transient interactions in signaling pathways to permanent interactions within stable complexes.  ...  AQ3 tein function prediction, protein complex discovery, and improving the reliability of protein-protein interactions.  ...  Spirin and Mirny [25] explored two methods of finding densely connected subgraphs in a protein interaction network, one of which is to renumerate all cliques in the network.  ... 
doi:10.1007/978-94-007-0881-5_13 fatcat:rvyz7lbb6nf6fcin67rjnczuva
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