Multitask learning for biomedical named entity recognition with cross-sharing structure

CollaboNet: collaboration of deep neural networks for biomedical named entity recognition

(2019) Wonjin Yoon et al.   BMC BIOINFORMATICS

Linking drug target and pathway activation for effective therapy using multi-task learning

(2018) Mi Yang et al.   Scientific Reports

Cross-type biomedical named entity recognition with deep multi-task learning

(2018) Xuan Wang et al.   BIOINFORMATICS

Identifying RNA-binding proteins using multi-label deep learning

(2018) Xiaoyong Pan et al.   Science China-Information Sciences

Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task

(2016) Chih-Hsuan Wei et al.   Database-The Journal of Biological Databases and Curation

Mining strong relevance between heterogeneous entities from unstructured biomedical data

(2015) Ming Ji et al.   DATA MINING AND KNOWLEDGE DISCOVERY

Multitasking models for quantitative structure–biological effect relationships: current status and future perspectives to speed up drug discovery

(2015) Alejandro Speck-Planche et al.   Expert Opinion on Drug Discovery

CHEMDNER system with mixed conditional random fields and multi-scale word clustering

(2015) Yanan Lu et al.   Journal of Cheminformatics

tmChem: a high performance approach for chemical named entity recognition and normalization

(2015) Robert Leaman et al.   Journal of Cheminformatics

Dynamic protein interaction network construction and applications

(2013) Jianxin Wang et al.   PROTEOMICS

LINNAEUS: A species name identification system for biomedical literature

(2010) Martin Gerner et al.   BMC BIOINFORMATICS