becas statistics

info info

Citations per year

Number of citations per year for the bioinformatics software tool becas
info

Tool usage distribution map

This map represents all the scientific publications referring to becas per scientific context
info info

Associated diseases

This word cloud represents becas usage per disease context
info

Popular tool citations

chevron_left Text annotation chevron_right
Want to access the full stats & trends on this tool?

Protocols

becas specifications

Information


Unique identifier OMICS_01173
Name becas
Alternative name Biomedical Concept Annotation System
Interface Web user interface
Restrictions to use Academic or non-commercial use
Computer skills Basic
Stability Stable
Maintained Yes

Maintainer


  • person_outline José Luís Oliveira

Publication for Biomedical Concept Annotation System

becas citations

 (11)
call_split

A semantic based workflow for biomedical literature annotation

2017
PMCID: 5691355
PMID: 29220478
DOI: 10.1093/database/bax088
call_split See protocol

[…] elect the desired output. With this external support, services such as BioPortal Annotator () (e.g. service: ‘http://data.bioontology.org/annotator?apikey = XXXX’, query: ‘[*][email protected]’) or BeCAS () (e.g. service: ‘http://bioinformatics.ua.pt/becas/api/text/annotate’, query: ‘*.*.refs’) can be easily integrated, providing an enhanced incorporation of the annotated data and improved simpl […]

library_books

Semantic annotation in biomedicine: the current landscape

2017
J Biomed Semantics
PMCID: 5610427
PMID: 28938912
DOI: 10.1186/s13326-017-0153-x

[…] rect annotations. The NCBO annotator is unique in its approach to associate concept mentions with multiple concepts, instead of finding one concept that would be the best match for the given context. BioMedical Concept Annotation System ( BeCAS ) [] is a Web-based tool for semantic annotation of biomedical texts, primarily biomedical research papers. Besides being available through a Web-based use […]

call_split

A rule based named entity recognition method for knowledge extraction of evidence based dietary recommendations

2017
PLoS One
PMCID: 5482438
PMID: 28644863
DOI: 10.1371/journal.pone.0179488
call_split See protocol

[…] n, teaspoon, etc. are added.For the Nutrient and the Food entity, dictionaries are constructed using the outputs of different NERs appropriate for the entity.For the Nutrient entity, a combination of becas API [], becas[chemicals] API [] and a semantic tagger, known as USAS online English semantic tagger [–], is used. Both, becas and becas[chemicals], are web-services-based and corpus-based NER de […]

library_books

The ChEMBL database in 2017

2016
Nucleic Acids Res
PMCID: 5210557
PMID: 27899562
DOI: 10.1093/nar/gkw1074

[…] ication (http://www.whocc.no/atc_ddd_index/) () and ClinicalTrials.gov (https://clinicaltrials.gov) (). Since these resources mainly provide free text information, a combination of text-mining (using BeCAS ()), automated mapping and manual curation/validation is used to identify the indication terms and assign the corresponding disease terms in the Medical Subject Headings (MeSH) vocabulary (https […]

library_books

Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain Specific Terminological Resource

2016
PLoS One
PMCID: 5028053
PMID: 27643689
DOI: 10.1371/journal.pone.0162287

[…] o the task of normalising entity mentions in clinical narrative text [, ].We have applied two terminology-driven baselines, i.e., the mature and highly used MetaMap [], and the more recently released BeCAS [], both of which firstly split the input text into sentences, and then identify the noun phrases in each sentence. Entity mentions are found by matching these noun phrases against concept synon […]

library_books

Coreference resolution improves extraction of Biological Expression Language statements from texts

2016
PMCID: 4930833
PMID: 27374122
DOI: 10.1093/database/baw076

[…] s and abundance functions, a rule-based approach for entity normalisation, and a statistical parser for classification of relationships. The system S5 () used existing systems such as PubTator () and BeCAS () for identification of biomedical concepts, a dictionary lookup method for entity normalisation and a rule-based approach for extraction of biological events. When incorporating coreference re […]


Want to access the full list of citations?
becas institution(s)
DETI/IEETA, University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal

becas reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review becas