A computational framework for distinguishing direct versus indirect interactions in human functional protein-protein interaction networks.

ABSTRACT: Recognition of indirect interactions is instrumental to in silico reconstruction of signaling pathways and sheds light on the exploration of unknown physical paths between two indirectly interacting genes. However, very limited computational methods have explicitly exploited the indirect interactions with experimental evidence thus far. In this work, we attempt to distinguish direct versus indirect interactions in human functional protein-protein interaction (PPI) networks via a predictive l₂-regularized logistic regression model built on the experimental data. The l₂-regularized logistic regression method is adopted to counteract the potential homolog noise and reduce the computational complexity on large training data. Computational results show that the proposed mo

SUBMITTER: Mei S 

PROVIDER: S-EPMC7238765 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature