TY - JOUR

T1 - EXTRACT

T2 - interactive extraction of environment metadata and term suggestion for metagenomic sample annotation

AU - Pafilis, Evangelos

AU - Buttigieg, Pier Luigi

AU - Ferrell, Barbra

AU - Pereira, Emiliano

AU - Schnetzer, Julia

AU - Arvanitidis, Christos

AU - Jensen, Lars Juhl

N1 - © The Author(s) 2016. Published by Oxford University Press.

PY - 2016

Y1 - 2016

N2 - The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have therefore developed an interactive annotation tool, EXTRACT, which helps curators identify and extract standard-compliant terms for annotation of metagenomic records and other samples. Behind its web-based user interface, the system combines published methods for named entity recognition of environment, organism, tissue and disease terms. The evaluators in the BioCreative V Interactive Annotation Task found the system to be intuitive, useful, well documented and sufficiently accurate to be helpful in spotting relevant text passages and extracting organism and environment terms. Comparison of fully manual and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed.Database URL: https://extract.hcmr.gr/.

AB - The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have therefore developed an interactive annotation tool, EXTRACT, which helps curators identify and extract standard-compliant terms for annotation of metagenomic records and other samples. Behind its web-based user interface, the system combines published methods for named entity recognition of environment, organism, tissue and disease terms. The evaluators in the BioCreative V Interactive Annotation Task found the system to be intuitive, useful, well documented and sufficiently accurate to be helpful in spotting relevant text passages and extracting organism and environment terms. Comparison of fully manual and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed.Database URL: https://extract.hcmr.gr/.

U2 - 10.1093/database/baw005

DO - 10.1093/database/baw005

M3 - Journal article

C2 - 26896844

VL - 2016

JO - Database : the journal of biological databases and curation

JF - Database : the journal of biological databases and curation

SN - 1758-0463

M1 - baw005

ER -