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Network based subcellular localization prediction for multi-label proteins | IEEE Conference Publication | IEEE Xplore

Network based subcellular localization prediction for multi-label proteins


Abstract:

Many proteins are sorted to multiple subcellular localizations within the cell. However, computational prediction of multi-location proteins remains a challenging task. H...Show More

Abstract:

Many proteins are sorted to multiple subcellular localizations within the cell. However, computational prediction of multi-location proteins remains a challenging task. Here we applied a logistic regression and diffusion kernel based algorithm NetLoc for predicting multiplex proteins and explored its capability and limitations. Experiment shows that the overall and true success rates for physical protein-protein interaction network are 65% and 41% respectively, and for mixed PPI network these values are 88% and 75% respectively. Our study also showed that the performance of NetLoc in predicting protein localization is limited by the network characteristics such as ratio of the number of co-localized protein-protein interactions (coPPI) to the number of non-co-localized PPI (ncPPI) and the density of annotated coPPI in the network. For a given network with a specific number of proteins, NetLoc performance increases with higher coPPI/ncPPI ratio and higher density of annotated coPPI.
Date of Conference: 12-15 November 2011
Date Added to IEEE Xplore: 26 December 2011
ISBN Information:
Conference Location: Atlanta, GA, USA

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