GOCat,
the Gene Ontology Categorizer


GOCat dictionary based computes similarities between an input text and the Gene Ontology (concepts and synonyms).
GOCat machine learning computes similarities between an input text and already curated instances contained in its knowledge base derived from GOA in order to predict GO concepts. A figure is worth a thousand words.

Please feel free to test GOCat: just type a free text (or an abstract), choose a model, and run ! You also can try GOCat4FT, a complete pipeline for curation with full texts.

Your text :
Model : Dictionary-Based (browser)
Machine Learning (predictive)
Mixed




Publication
Managing the data deluge: data-driven GO category assignment improves while complexity of functional annotation increases
Gobeill J, Pasche E, Vishnyakova D and Ruch P
Database (2013), doi: 10.1093/database/bat041

GOCat as an API
Please use eagl.unige.ch/GOCat/result.jsp for automatic requests.
Parameters are queryTXT=[inputText] (the query), json (for a json output), and cat=[db|ml|mx] for the model.
Example : eagl.unige.ch/GOCat/result.jsp?queryTXT=p53 function&cat=ml&json

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