NDLI: Complex detection from PPI data using ensemble method

Content Provider	Springer Nature Link
Author	Nagi, Sajid Bhattacharyya, Dhruba K. Kalita, Jugal K.
Copyright Year	2016
Abstract	Many algorithms have been proposed recently to detect protein complexes in protein–protein interaction (PPI) networks. Most proteins form complexes to accomplish biological functions such as transcription of DNA, translation of mRNA and cell growth. Since proteins perform their tasks by interacting with each other, determining these protein–protein interactions is an important task. Traditional clustering approaches for protein complex identification cannot deal with noisy and incomplete PPI data and dependent on information from a single source. Since the noise in the interaction datasets hampers the detection of accurate protein complexes, we propose an ensemble approach for protein complex detection that attempts to combine information from Gene Ontology at the time of complex detection. The PPI data network is taken as input by several baseline complex detection algorithms to generate protein complexes. The protein complexes are then subsequently combined by the proposed ensemble using a consensus building module for the purpose of identifying meaningful complexes. The protein complexes thus predicted by the ensemble are evaluated by comparing them to a set of gold standard protein complexes and their biological relevance established using a co-localization score.
Starting Page	1
Ending Page	13
Page Count	13
File Format	PDF
ISSN	21926662
Journal	Network Modeling Analysis in Health Informatics and Bioinformatics
Volume Number	6
Issue Number	1
e-ISSN	21926670
Language	English
Publisher	Springer Vienna
Publisher Date	2016-12-30
Publisher Place	Vienna
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Computational Biology/Bioinformatics Protein complex prediction Protein interaction network Health Informatics Empirical study of proteins Bioinformatics Ensemble clustering Applications of Graph Theory and Complex Networks
Content Type	Text
Resource Type	Article
Subject	Urology

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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
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