Probability weighted ensemble transfer learning for predicting interactions between HIV-1 and human proteins.

ABSTRACT: Reconstruction of host-pathogen protein interaction networks is of great significance to reveal the underlying microbic pathogenesis. However, the current experimentally-derived networks are generally small and should be augmented by computational methods for less-biased biological inference. From the point of view of computational modelling, data scarcity, data unavailability and negative data sampling are the three major problems for host-pathogen protein interaction networks reconstruction. In this work, we are motivated to address the three concerns and propose a probability weighted ensemble transfer learning model for HIV-human protein interaction prediction (PWEN-TLM), where support vector machine (SVM) is adopted as the individual classifier of the ensemble model. In the model, dat

SUBMITTER: Mei S 

PROVIDER: S-EPMC3832534 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature