Abstract
BioC is a simple XML format for text, annotations and relations, and was developed to achieve interoperability for biomedical text processing. Following the success of BioC in BioCreative IV, the BioCreative V BioC track addressed a collaborative task to build an assistant system for BioGRID curation. In this paper, we describe the framework of the collaborative BioC task and discuss our findings based on the user survey. This track consisted of eight subtasks including gene/protein/organism named entity recognition, protein–protein/genetic interaction passage identification and annotation visualization. Using BioC as their data-sharing and communication medium, nine teams, world-wide, participated and contributed either new methods or improvements of existing tools to address different subtasks of the BioC track. Results from different teams were shared in BioC and made available to other teams as they addressed different subtasks of the track. In the end, all submitted runs were merged using a machine learning classifier to produce an optimized output. The biocurator assistant system was evaluated by four BioGRID curators in terms of practical usability. The curators’ feedback was overall positive and highlighted the user-friendly design and the convenient gene/protein curation tool based on text mining.Database URL: http://www.biocreative.org/tasks/biocreative-v/track-1-bioc/
Highlights
Understanding the organization of molecular interactions is fundamental for comprehending how cellular networks regulate homeostasis and cellular response to external stimuli [1]
Full text articles were processed for gene, protein and species mention recognition and normalization, and the outputs were submitted to the task organizers for availability to the teams working on the other tasks and inclusion in the complete biocurator assistant system
BioGRID curators were asked to rate the usefulness of the system and its functionality on a scale of 1 to 5 and were encouraged to provide feedback about aspects that would benefit from further improvement
Summary
Understanding the organization of molecular interactions is fundamental for comprehending how cellular networks regulate homeostasis and cellular response to external stimuli [1]. The purpose of the BioC [6] track in BioCreative V was to create BioC-compatible modules which complement each other and can be seamlessly integrated into a system that assists BioGRID curators. BioC is a minimalist approach to interoperability for biomedical text mining. The PPI track [7,8,9] was divided into subcategories and each task was addressed independently, i.e. article classification, interaction pair extraction, interaction sentence classification and experimental method identification. The user interactive track (IAT) [10,11,12] promoted the development of annotation systems that can assist in biocuration tasks by bringing text mining tool developers and database curators together. Probably due to lack of interoperability or sub-optimal performance, no attempt was made to integrate such modules into a single annotation tool
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
