Finding motif pairs in the interactions between heterogeneous proteins via bootstrapping and boosting.

ABSTRACT:

Background

Supervised learning and many stochastic methods for predicting protein-protein interactions require both negative and positive interactions in the training data set. Unlike positive interactions, negative interactions cannot be readily obtained from interaction data, so these must be generated. In protein-protein interactions and other molecular interactions as well, taking all non-positive interactions as negative interactions produces too many negative interactions for the positive interactions. Random selection from non-positive interactions is unsuitable, since the selected data may not reflect the original distribution of data.

Results

We developed a bootstrapping algorithm for generating a negative data set of arbitrary size from protein-protein interaction

SUBMITTER: Kim J 

PROVIDER: S-EPMC2648735 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature