Tagsty: augmented knowledge from community-based annotations on protein sequences

Authors:
Leyla Jael Garcia Castro;Alexander Garcia
Affiliations:
European Bioinformatics Institute, Hinxton, UK and Universität der Bundeswehr, Neubiberg, Germany;University of Arkansas, Biomedical Informatics, Medical Center, Little Rock, AR
Venue:
Proceedings of the 4th International Workshop on Semantic Web Applications and Tools for the Life Sciences
Year:
2011

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Abstract

We have reviewed different approaches on community-based annotation on protein and gene sequences, mainly relying on the wiki paradigms. Currently such approaches are not fully exploiting the social component that naturally emerges within communities. We propose a model, namely Tagsty, that enables a community to semantically annotate protein sequences while benefit from the emerged social network. We argue that such environment lowers the barriers on extracting semantic content from social platforms, enables users to share new content, and facilitates knowledge discovery. We also present an architecture supporting our proposal.