Paper Info
Title
Guideline Design Of An Active Gene Annotation Corpus For The Purpose Of Drug Repurposing
Abstract
In order to develop a gold corpus for Biomedical Natural Language Processing community for the sake of knowledge discovery in drug repurposing, an active gene annotation corpus (AGAC) was developed in this research. Five semantic trigger labels and three root regulatory trigger labels were designed as molecular-and cell-level biological entity annotations, which focused on the information of function change in biological processes resulted from mutated genes. In addition, predicates 'ThemeOf' and 'CauseOf' were as well annotated manually for the semantic knowledge extraction. Eventually, roles of gene mutation including gain of function (GOF) and loss of function (LOF) were curated through the AGAC annotation guideline. The information from AGAC annotation effectively bridge the association between mutation, gene, drug and disease, and make it possible to predict new drug direction in a large scale.AGAC corpus availability: The corpus is available in PubAnnotation platform(1).
Year
DOI
Venue
2018
10.1109/CISP-BMEI.2018.8633253
2018 11TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2018)
Field
DocType
Citations 
Semantic memory,Drug repositioning,Loss function,Annotation,Pattern recognition,Computer science,Artificial intelligence,Knowledge extraction,Computational biology,Guideline,Semantics,Gene Annotation
Conference
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Yuxing Wang104.39
Xinzhi Yao200.34
Kaiyin Zhou302.70
Xuan Qin400.68
Jin-Dong Kim5170592.21
Kevin Bretonnel Cohen630218.50
Jingbo Xia7147.50