Paper Info
Title
Mining clinical attributes of genomic variants through assisted literature curation in Egas.
Abstract
The veritable deluge of biological data over recent years has led to the establishment of a considerable number of knowledge resources that compile curated information extracted from the literature and store it in structured form, facilitating its use and exploitation. In this article, we focus on the curation of inherited genetic variants and associated clinical attributes, such as zygosity, penetrance or inheritance mode, and describe the use of Egas for this task. Egas is a web-based platform for text-mining assisted literature curation that focuses on usability through modern design solutions and simple user interactions. Egas offers a flexible and customizable tool that allows defining the concept types and relations of interest for a given annotation task, as well as the ontologies used for normalizing each concept type. Further, annotations may be performed on raw documents or on the results of automated concept identification and relation extraction tools. Users can inspect, correct or remove automatic text-mining results, manually add new annotations, and export the results to standard formats. Egas is compatible with the most recent versions of Google Chrome, Mozilla Firefox, Internet Explorer and Safari and is available for use at https://demo.bmd-software.com/egas/.
Year
DOI
Venue
2016
10.1093/database/baw096
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
Field
DocType
Volume
Ontology (information science),Data mining,Biological data,World Wide Web,Annotation,Information retrieval,Computer science,Usability,Compiler,Bioinformatics,Relationship extraction,The Internet
Journal
2016
ISSN
Citations 
PageRank 
1758-0463
3
0.40
References 
Authors
22
7
Name
Order
Citations
PageRank
Sérgio Matos141529.51
David Campos221910.69
Renato P. Pinho381.30
Raquel M. Silva442.11
Matthew E. Mort531.76
David N Cooper68013.72
José Luis Oliveira776084.03