Abstract
With the overwhelming amount of biomedical textual information being produced, several manual curation efforts have been set up to extract and store concepts and their relationships into structured resources. As manual annotation is a demanding and expensive task, computerized solutions were developed to perform such tasks automatically. However, high-end information extraction techniques are still not widely used by biomedical research communities, mainly because of the lack of standards and limitations in usability. Interactive annotation tools intend to fill this gap, taking advantage of automatic techniques and existing knowledge bases to assist expert curators in their daily tasks. This article presents Egas, a web-based platform for biomedical text mining and assisted curation with highly usable interfaces for manual and automatic in-line annotation of concepts and relations. A comprehensive set of de facto standard knowledge bases are integrated and indexed to provide straightforward concept normalization features. Real-time collaboration and conversation functionalities allow discussing details of the annotation task as well as providing instant feedback of curator’s interactions. Egas also provides interfaces for on-demand management of the annotation task settings and guidelines, and supports standard formats and literature services to import and export documents. By taking advantage of Egas, we participated in the BioCreative IV interactive annotation task, targeting the assisted identification of protein–protein interactions described in PubMed abstracts related to neuropathological disorders. When evaluated by expert curators, it obtained positive scores in terms of usability, reliability and performance. These results, together with the provided innovative features, place Egas as a state-of-the-art solution for fast and accurate curation of information, facilitating the task of creating and updating knowledge bases and annotated resources.Database URL: http://bioinformatics.ua.pt/egas
Highlights
A growing amount of biomedical data is continuously being produced, resulting largely from the widespread application of high-throughput techniques, such as gene and protein analysis
By taking advantage of Egas, we participated in the BioCreative IV interactive annotation task, targeting the assisted identification of protein–protein interactions described in PubMed abstracts related to neuropathological disorders
(3) argue that manually curating and fulfilling some genomic resources may take decades to be completed. These factors have naturally led to an increasing interest in the application of text mining (TM) systems to perform those tasks automatically
Summary
A growing amount of biomedical data is continuously being produced, resulting largely from the widespread application of high-throughput techniques, such as gene and protein analysis. [3] argue that manually curating and fulfilling some genomic resources may take decades to be completed These factors have naturally led to an increasing interest in the application of text mining (TM) systems to perform those tasks automatically. One must carefully analyse the provided automatic information and correct the existing mistakes In this perspective, various studies have shown that using automatic solutions to assist biocurators delivers improved curation times [9, 10]. It is important to develop interactive solutions that take advantage of automatic computational solutions and existing knowledge resources to assist expert curators in their daily tasks. By taking advantage of such interactive solutions, biocurators can and more effectively keep current knowledge bases updated and generate annotated data to develop and evaluate automatic solutions
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