BioCreative shared task
Project Information
- Discipline
- Computer Science (401)
- Subdiscipline
- 11.01 Computer and Information Sciences, General
- Orientation
- Research
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 MeritWe 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 ImpactsIf 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.
Project Contact
- Project Lead
- Feifan Liu (sedulous)
- Project Manager
- Feifan Liu (sedulous)
Resource Requirements
- Hardware System
-
- Not sure
computing purpose
Scale of Usesmall scale
Project Timeline
- Submitted
- 04/21/2013 - 13:11