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ActiveMotif: Interactive Motif Discovery with Human Feedback

Title
ActiveMotif: Interactive Motif Discovery with Human Feedback
Author
김영훈
Issue Date
2017-07
Publisher
IEEE
Citation
2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Page. 2736-2739
Abstract
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.
URI
https://ieeexplore.ieee.org/document/8037423http://repository.hanyang.ac.kr/handle/20.500.11754/103484
ISBN
978-1-5090-2809-2
ISSN
1558-4615
DOI
10.1109/EMBC.2017.8037423
Appears in Collections:
COLLEGE OF COMPUTING[E] > COMPUTER SCIENCE(소프트웨어학부) > Articles
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