Mining microbe–disease interactions from literature via a transfer learning model
Background: Interactions of microbes and diseases are of great importance for biomedical research. However, large-scale of microbe–disease interactions are hidden in the biomedical literature. The structured databases for microbe–disease interactions are in limited amounts. In this paper, we aim to...
Main Authors: | Chen, J.X (Author), Qiu, Y. (Author), Wu, C. (Author), Xiao, X. (Author), Yang, C. (Author), Yi, J. (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
BioMed Central Ltd
2021
|
Subjects: | |
Online Access: | View Fulltext in Publisher |
Similar Items
-
Mining microbe–disease interactions from literature via a transfer learning model
by: Chengkun Wu, et al.
Published: (2021-09-01) -
Statistical principle-based approach for gene and protein related object recognition
by: Po-Ting Lai, et al.
Published: (2018-12-01) -
A Boundary Assembling Method for Nested Biomedical Named Entity Recognition
by: Yanping Chen, et al.
Published: (2020-01-01) -
A hybrid deep learning framework for bacterial named entity recognition with domain features
by: Xusheng Li, et al.
Published: (2019-12-01) -
Entity recognition in the biomedical domain using a hybrid approach
by: Marco Basaldella, et al.
Published: (2017-11-01)