These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Network based prediction of protein localisation using diffusion kernel.
    Author: Mondal A, Hu J.
    Journal: Int J Data Min Bioinform; 2014; 9(4):386-400. PubMed ID: 25757246.
    Abstract:
    We present NetLoc, a novel diffusion Kernel-based Logistic Regression (KLR) algorithm for predicting protein subcellular localisation using four types of protein networks including physical PPI networks, genetic Protein-Protein Interaction (PPI) networks, mixed PPI networks and co-expression networks. NetLoc is applied to yeast protein localisation prediction. The results showed that protein networks can provide rich information for protein localisation prediction, achieving Area Under Curve (AUC) score of 0.93. We also showed that networks with high connectivity and high percentage of co-localised PPI lead to better prediction performance. Investigation showed that NetLoc is a very robust approach which can produce good performance (AUC = 0.75) only using 30% of original interactions and capable of producing overall accuracy greater than 0.5 only with 20% annotation coverage. Compared to the previous network feature based prediction algorithm which achieved AUC scores of 0.49 and 0.52 on the yeast PPI network, NetLoc achieved significantly better overall performance with the AUC of 0.74.
    [Abstract] [Full Text] [Related] [New Search]