SIA: A Scalable Interoperable Annotation Server for Biomedical Named Entities

04/08/2020
by   Johannes Kirschnick, et al.
0

Recent years showed a strong increase in biomedical sciences and an inherent increase in publication volume. Extraction of specific information from these sources requires highly sophisticated text mining and information extraction tools. However, the integration of freely available tools into customized workflows is often cumbersome and difficult. We describe SIA (Scalable Interoperable Annotation Server), our contribution to the BeCalm-Technical interoperability and performance of annotation servers (BeCalm-TIPS) task, a scalable, extensible, and robust annotation service. The system currently covers six named entity types (i.e., Chemicals, Diseases, Genes, miRNA, Mutations, and Organisms) and is freely available under Apache 2.0 license at https://github.com/Erechtheus/sia.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/17/2020

HunFlair: An Easy-to-Use Tool for State-of-the-Art Biomedical Named Entity Recognition

Summary: Named Entity Recognition (NER) is an important step in biomedic...
research
10/21/2022

NEREL-BIO: A Dataset of Biomedical Abstracts Annotated with Nested Named Entities

This paper describes NEREL-BIO – an annotation scheme and corpus of PubM...
research
01/15/2020

Transfer learning for biomedical named entity recognition with neural networks.

Motivation The explosive increase of biomedical literature has made i...
research
03/16/2020

Parallel sequence tagging for concept recognition

Motivation: Named Entity Recognition (NER) and Normalisation (NEN) are c...
research
10/13/2020

Annotationsaurus: A Searchable Directory of Annotation Tools

Manual annotation of textual documents is a necessary task when construc...
research
04/27/2020

Automatic Textual Evidence Mining in COVID-19 Literature

We created this EVIDENCEMINER system for automatic textual evidence mini...
research
11/12/2018

Bio-YODIE: A Named Entity Linking System for Biomedical Text

Ever-expanding volumes of biomedical text require automated semantic ann...

Please sign up or login with your details

Forgot password? Click here to reset