NDLI: A New Method for Detecting Protein Complexes based on the Three Node Cliques

Content Provider	IEEE Xplore Digital Library
Author	Wei Zhang Xiufen Zou
Copyright Year	2004
Abstract	The identification of protein complexes in protein-protein interaction (PPI) networks is fundamental for understanding biological processes and cellular molecular mechanisms. Many graph computational algorithms have been proposed to identify protein complexes from PPI networks by detecting densely connected groups of proteins. These algorithms assess the density of subgraphs through evaluation of the sum of individual edges or nodes; thus, incomplete and inaccurate measures may miss meaningful biological protein complexes with functional significance. In this study, we propose a novel method for assessing the compactness of local subnetworks by measuring the number of three node cliques. The present method detects each optimal cluster by growing a seed and maximizing the compactness function. To demonstrate the efficacy of the new proposed method, we evaluate its performance using five PPI networks on three reference sets of yeast protein complexes with five different measurements and compare the performance of the proposed method with four state-of-the-art methods. The results show that the protein complexes generated by the proposed method are of better quality than those generated by four classic methods. Therefore, the new proposed method is effective and useful for detecting protein complexes in PPI networks.
Sponsorship	IEEE Computer Society
Starting Page	879
Ending Page	886
Page Count	8
File Size	525225
File Format	PDF
ISSN	15455963
Volume Number	12
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Proteins Clustering algorithms Bioinformatics Computational biology data Processing protein complexes protein-protein interaction networks three node cliques data processing Protein complexes
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Genetics Biotechnology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A new method for detecting protein complexes based on the three node cliques

A Coclustering Approach for Mining Large Protein-Protein Interaction Networks

Detecting Protein Complexes from Signed Protein-Protein Interaction Networks

A Fast Hierarchical Clustering Algorithm for Functional Modules Discovery in Protein Interaction Networks

Detecting Protein Complexes Based on Uncertain Graph Model

A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks

From Function to Interaction: A New Paradigm for Accurately Predicting Protein Complexes Based on Protein-to-Protein Interaction Networks

Identification of Protein Complexes Using Weighted PageRank-Nibble Algorithm and Core-Attachment Structure

Clustering 100,000 Protein Structure Decoys in Minutes

A New Method for Detecting Protein Complexes based on the Three Node Cliques

Similar Documents

A new method for detecting protein complexes based on the three node cliques

A Coclustering Approach for Mining Large Protein-Protein Interaction Networks

Detecting Protein Complexes from Signed Protein-Protein Interaction Networks

A Fast Hierarchical Clustering Algorithm for Functional Modules Discovery in Protein Interaction Networks

Detecting Protein Complexes Based on Uncertain Graph Model

A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks

From Function to Interaction: A New Paradigm for Accurately Predicting Protein Complexes Based on Protein-to-Protein Interaction Networks

Identification of Protein Complexes Using Weighted PageRank-Nibble Algorithm and Core-Attachment Structure

Clustering 100,000 Protein Structure Decoys in Minutes

A New Method for Detecting Protein Complexes based on the Three Node Cliques