research-article

A collective NMF method for detecting protein functional module from multiple data sources

Authors:

Aidong ZhangAuthors Info & Claims

BCB '12: Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine

Pages 655 - 660

https://doi.org/10.1145/2382936.2383053

Published: 07 October 2012 Publication History

Abstract

Detecting functional modules from protein-protein interaction (PPI) networks is an active research area with many practical applications. However, there is always a critical concern on the false PPI interactions which are derived from the high-throughput experiments and the unsatisfactory results obtained from single PPI network with severe information insufficiency. To address this problem, we propose a Collective Non-negative Matrix Factorization (CoNMF) based soft clustering method which efficiently integrates information of gene ontology (GO), gene expression data and PPI networks. In our method, the three data sources are formed into two graphs with similarity adjacency matrices and these graphs are approximated by a matrix factorization with their common factor which provides the straight-forward interpretation of clustering results. Extensive experiments show that we can improve the module detection performance by integrating multiple biological data sources and that CoNMF yields superior results compared to other multiple data sources fusion methods by identifying a larger number of more precise protein modules with actual biological meaning and certain degree of overlapping.

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Cited By

Guven E(2023)Decision of the Optimal Rank of a Nonnegative Matrix Factorization Model for Gene Expression Data Sets Utilizing the Unit Invariant Knee Method: Development and Evaluation of the Elbow Method for Rank SelectionJMIR Bioinformatics and Biotechnology10.2196/436654(e43665)Online publication date: 6-Jun-2023
https://doi.org/10.2196/43665
Jin DHe JChai BHe D(2021)Semi-supervised community detection on attributed networks using non-negative matrix tri-factorization with node popularityFrontiers of Computer Science10.1007/s11704-020-9203-015:4Online publication date: 11-Feb-2021
https://doi.org/10.1007/s11704-020-9203-0
Cao BDeng SQin HDing PChen SLi G(2018)Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein–Protein Interaction NetworkMolecules10.3390/molecules2306146023:6(1460)Online publication date: 15-Jun-2018
https://doi.org/10.3390/molecules23061460
Show More Cited By

Index Terms

A collective NMF method for detecting protein functional module from multiple data sources
1. Applied computing
  1. Life and medical sciences
2. Information systems
  1. Information systems applications
    1. Data mining

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Published In

cover image ACM Conferences

BCB '12: Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine

October 2012

725 pages

ISBN:9781450316705

DOI:10.1145/2382936

General Chair:
Sanjay Ranka
University of Florida
,
Program Chairs:
Tamer Kahveci
University of Florida
,
Mona Singh
Princeton University

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGBio: ACM Special Interest Group on Bioinformatics

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 October 2012

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BCB' 12

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SIGBio

BCB' 12: ACM International Conference on Bioinformatics, Computational Biology and Biomedicine

October 7 - 10, 2012

Florida, Orlando

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BCB '12 Paper Acceptance Rate 33 of 159 submissions, 21%;

Overall Acceptance Rate 254 of 885 submissions, 29%

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Cited By

Guven E(2023)Decision of the Optimal Rank of a Nonnegative Matrix Factorization Model for Gene Expression Data Sets Utilizing the Unit Invariant Knee Method: Development and Evaluation of the Elbow Method for Rank SelectionJMIR Bioinformatics and Biotechnology10.2196/436654(e43665)Online publication date: 6-Jun-2023
https://doi.org/10.2196/43665
Jin DHe JChai BHe D(2021)Semi-supervised community detection on attributed networks using non-negative matrix tri-factorization with node popularityFrontiers of Computer Science10.1007/s11704-020-9203-015:4Online publication date: 11-Feb-2021
https://doi.org/10.1007/s11704-020-9203-0
Cao BDeng SQin HDing PChen SLi G(2018)Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein–Protein Interaction NetworkMolecules10.3390/molecules2306146023:6(1460)Online publication date: 15-Jun-2018
https://doi.org/10.3390/molecules23061460
Liu GChai BYang KYu JZhou X(2018)Overlapping functional modules detection in PPI network with pair‐wise constrained non‐negative matrix tri‐factorisationIET Systems Biology10.1049/iet-syb.2017.008412:2(45-54)Online publication date: 7-Feb-2018
https://doi.org/10.1049/iet-syb.2017.0084
Li XYe YNg MWu Q(2013)MultiFacTV: module detection from higher-order time series biological dataBMC Genomics10.1186/1471-2164-14-S4-S214:S4Online publication date: 1-Oct-2013
https://doi.org/10.1186/1471-2164-14-S4-S2

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