Background: The biomedical literature is the primary information source for manual protein-
protein interaction annotations. Text-mining systems have been implemented to extract …

We introduce a relation extraction method to identify the sentences in biomedical text that
indicate an interaction among the protein names mentioned. Our approach is based on the …

Since complete redundancy between extant duplicates (paralogs) is evolutionarily
unfavorable, some degree of functional congruency is eventually lost. However, in budding …

Extracting semantic relationships about biomedical entities in a sentence is a typical task in
biomedical information extraction. Because a sentence usually contains several named …

Protein–protein interactions play a key role in various aspects of the structural and functional
organization of the cell. Knowledge about them unveils the molecular mechanisms of …

Protein complexes, consisting of stable protein-protein interactions (PPIs), are ubiquitous
and essential to the proper conduct of all eukaryotic functional pathways, serving to …

Background Identifying protein-protein interactions (PPIs) from literature is an important step
in mining the function of individual proteins as well as their biological network. Since it is …

Semi-supervised classification is an interesting idea where classification models are learned
from both labeled and unlabeled data. It has several advantages over supervised …

Recent kernel-based PPI extraction systems achieve promising performance because of
their capability to capture structural syntactic information, but at the expense of …

This paper presents a novel method to extract Protein-Protein Interaction (PPI) information
from biomedical literatures based on Support Vector Machine (SVM) and K Nearest …