Protein phosphorylation is a central regulatory mechanism in signal transduction 
involved in most biological processes. Phosphorylation of a protein may lead to 
activation or repression of its activity, alternative subcellular location and 
interaction with different binding partners. Extracting this type of information 
from scientific literature is critical for connecting phosphorylated proteins 
with kinases and interaction partners, along with their functional outcomes, for 
knowledge discovery from phosphorylation protein networks. We have developed the 
Extracting Functional Impact of Phosphorylation (eFIP) text mining system, which 
combines several natural language processing techniques to find relevant 
abstracts mentioning phosphorylation of a given protein together with 
indications of protein-protein interactions (PPIs) and potential evidences for 
impact of phosphorylation on the PPIs. eFIP integrates our previously developed 
tools, Extracting Gene Related ABstracts (eGRAB) for document retrieval and name 
disambiguation, Rule-based LIterature Mining System (RLIMS-P) for Protein 
Phosphorylation for extraction of phosphorylation information, a PPI module to 
detect PPIs involving phosphorylated proteins and an impact module for relation 
extraction. The text mining system has been integrated into the curation 
workflow of the Protein Ontology (PRO) to capture knowledge about phosphorylated 
proteins. The eFIP web interface accepts gene/protein names or identifiers, or 
PubMed identifiers as input, and displays results as a ranked list of abstracts 
with sentence evidence and summary table, which can be exported in a spreadsheet 
upon result validation. As a participant in the BioCreative-2012 Interactive 
Text Mining track, the performance of eFIP was evaluated on document retrieval 
(F-measures of 78-100%), sentence-level information extraction (F-measures of 
70-80%) and document ranking (normalized discounted cumulative gain measures of 
93-100% and mean average precision of 0.86). The utility and usability of the 
eFIP web interface were also evaluated during the BioCreative Workshop. The use 
of the eFIP interface provided a significant speed-up (∼2.5-fold) for time to 
completion of the curation task. Additionally, eFIP significantly simplifies the 
task of finding relevant articles on PPI involving phosphorylated forms of a 
given protein.