κΉμν
2019-05-07T04:45:58Z
2019-05-07T04:45:58Z
2017-07
2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Page. 2736-2739
978-1-5090-2809-2
1558-4615
https://ieeexplore.ieee.org/document/8037423
https://repository.hanyang.ac.kr/handle/20.500.11754/103484
Motif detection, which is to discover short patterns involved in many important biological processes, has been recently raised as an important task in bioinformatics. The traditional algorithms to find a sequence motif have been developed using machine learning only without involving the experience and domain knowledge of human experts effectively. In this paper, we propose an interactive motif discovery system by introducing a new learning algorithm, by generalizing a well-known statistical motif model, whose inference can be shepherded by human feedback. © 2017 IEEE.
en_US
IEEE
ActiveMotif: Interactive Motif Discovery with Human Feedback
Article
10.1109/EMBC.2017.8037423
2736-2739
Kim, Y
Lee, W
Kim, K
20170103
E
COLLEGE OF COMPUTING[E]
DIVISION OF COMPUTER SCIENCE
nongaussian