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Scored protein-protein interaction to predict subcellular localizations for yeast using diffusion kernel
Conference
Mondal, AM, Hu, J. (2013). Scored protein-protein interaction to predict subcellular localizations for yeast using diffusion kernel .
EURO-PAR 2011 PARALLEL PROCESSING, PT 1,
8251 LNCS 647-655. 10.1007/978-3-642-45062-4_91
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Mondal, AM, Hu, J. (2013). Scored protein-protein interaction to predict subcellular localizations for yeast using diffusion kernel .
EURO-PAR 2011 PARALLEL PROCESSING, PT 1,
8251 LNCS 647-655. 10.1007/978-3-642-45062-4_91
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cited authors
Mondal, AM; Hu, J
authors
Mondal, Ananda
abstract
Network-based protein localization prediction is explored utilizing the protein-protein interaction score along with the network connectivity. Score-based diffusion kernel is introduced to solve the problem. Four different PPI networks, namely, co-expressed PPI, Genetic PPI, Physical PPI, and scored PPI are used for analysis. Our investigation shows that PPI score does have positive impact in predicting subcellular protein localization. At high average PPI score of 891, performance accuracy ranges from 0.78 for 'punctate composite' to 0.93 for 'nucleolus' and at low average PPI score of 169, performance accuracy ranges from 0.60 for 'cytoplasm' to 0.83 for 'mitochondrion'. © Springer-Verlag 2013.
publication date
December 1, 2013
published in
DISTRIBUTED COMPUTING (DISC 2014)
Book
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Digital Object Identifier (DOI)
https://doi.org/10.1007/978-3-642-45062-4_91
Additional Document Info
start page
647
end page
655
volume
8251 LNCS