BioCreative shared task

Project Details

Project Lead
Feifan Liu 
Project Manager
Feifan Liu 
Institution
University of Wisconsin Milwaukee, Computer Science  
Discipline
Computer Science (401) 
Subdiscipline
11.01 Computer and Information Sciences, General 

Abstract

There is a growing need for semi-automated GO curation techniques that will help database curators rapidly and accurately identify gene function information in full-length articles. This project is mainly for a classification task along this line, which will classify whether or not an article is relevant for GO curation.

Intellectual Merit

We hope, through participating this BioCreative task, to advance text-mining research in automatic GO prediction (ultimate goal) but also result in the development of methods and tools that can provide practical benefits to the GO curators (immediate benefits).

Broader Impacts

If this task is addressed successfully, it will broaden the dialog between GO curators and text mining developers and facilitate the use of high-performing systems in real-life GO curation during and after the challenge.

Scale of Use

small scale