Cargando…

Ferret: a sentence-based literature scanning system

BACKGROUND: The rapid pace of bioscience research makes it very challenging to track relevant articles in one’s area of interest. MEDLINE, a primary source for biomedical literature, offers access to more than 20 million citations with three-quarters of a million new ones added each year. Thus it is...

Descripción completa

Detalles Bibliográficos
Autores principales: Srinivasan, Padmini, Zhang, Xiao-Ning, Bouten, Roxane, Chang, Caren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4474359/
https://www.ncbi.nlm.nih.gov/pubmed/26091670
http://dx.doi.org/10.1186/s12859-015-0630-0
_version_ 1782377261402423296
author Srinivasan, Padmini
Zhang, Xiao-Ning
Bouten, Roxane
Chang, Caren
author_facet Srinivasan, Padmini
Zhang, Xiao-Ning
Bouten, Roxane
Chang, Caren
author_sort Srinivasan, Padmini
collection PubMed
description BACKGROUND: The rapid pace of bioscience research makes it very challenging to track relevant articles in one’s area of interest. MEDLINE, a primary source for biomedical literature, offers access to more than 20 million citations with three-quarters of a million new ones added each year. Thus it is not surprising to see active research in building new document retrieval and sentence retrieval systems. We present Ferret, a prototype retrieval system, designed to retrieve and rank sentences (and their documents) conveying gene-centric relationships of interest to a scientist. The prototype has several features. For example, it is designed to handle gene name ambiguity and perform query expansion. Inputs can be a list of genes with an optional list of keywords. Sentences are retrieved across species but the species discussed in the records are identified. Results are presented in the form of a heat map and sentences corresponding to specific cells of the heat map may be selected for display. Ferret is designed to assist bio scientists at different stages of research from early idea exploration to advanced analysis of results from bench experiments. RESULTS: Three live case studies in the field of plant biology are presented related to Arabidopsis thaliana. The first is to discover genes that may relate to the phenotype of open immature flower in Arabidopsis. The second case is about finding associations reported between ethylene signaling and a set of 300+ Arabidopsis genes. The third case is on searching for potential gene targets of an Arabidopsis transcription factor hypothesized to be involved in plant stress responses. Ferret was successful in finding valuable information in all three cases. In the first case the bZIP family of genes was identified. In the second case sentences indicating relevant associations were found in other species such as potato and jasmine. In the third sentences led to new research questions about the plant hormone salicylic acid. CONCLUSIONS: Ferret successfully retrieved relevant gene-centric sentences from PubMed records. The three case studies demonstrate end user satisfaction with the system.
format Online
Article
Text
id pubmed-4474359
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-44743592015-06-20 Ferret: a sentence-based literature scanning system Srinivasan, Padmini Zhang, Xiao-Ning Bouten, Roxane Chang, Caren BMC Bioinformatics Research Article BACKGROUND: The rapid pace of bioscience research makes it very challenging to track relevant articles in one’s area of interest. MEDLINE, a primary source for biomedical literature, offers access to more than 20 million citations with three-quarters of a million new ones added each year. Thus it is not surprising to see active research in building new document retrieval and sentence retrieval systems. We present Ferret, a prototype retrieval system, designed to retrieve and rank sentences (and their documents) conveying gene-centric relationships of interest to a scientist. The prototype has several features. For example, it is designed to handle gene name ambiguity and perform query expansion. Inputs can be a list of genes with an optional list of keywords. Sentences are retrieved across species but the species discussed in the records are identified. Results are presented in the form of a heat map and sentences corresponding to specific cells of the heat map may be selected for display. Ferret is designed to assist bio scientists at different stages of research from early idea exploration to advanced analysis of results from bench experiments. RESULTS: Three live case studies in the field of plant biology are presented related to Arabidopsis thaliana. The first is to discover genes that may relate to the phenotype of open immature flower in Arabidopsis. The second case is about finding associations reported between ethylene signaling and a set of 300+ Arabidopsis genes. The third case is on searching for potential gene targets of an Arabidopsis transcription factor hypothesized to be involved in plant stress responses. Ferret was successful in finding valuable information in all three cases. In the first case the bZIP family of genes was identified. In the second case sentences indicating relevant associations were found in other species such as potato and jasmine. In the third sentences led to new research questions about the plant hormone salicylic acid. CONCLUSIONS: Ferret successfully retrieved relevant gene-centric sentences from PubMed records. The three case studies demonstrate end user satisfaction with the system. BioMed Central 2015-06-20 /pmc/articles/PMC4474359/ /pubmed/26091670 http://dx.doi.org/10.1186/s12859-015-0630-0 Text en © Srinivasan et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Srinivasan, Padmini
Zhang, Xiao-Ning
Bouten, Roxane
Chang, Caren
Ferret: a sentence-based literature scanning system
title Ferret: a sentence-based literature scanning system
title_full Ferret: a sentence-based literature scanning system
title_fullStr Ferret: a sentence-based literature scanning system
title_full_unstemmed Ferret: a sentence-based literature scanning system
title_short Ferret: a sentence-based literature scanning system
title_sort ferret: a sentence-based literature scanning system
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4474359/
https://www.ncbi.nlm.nih.gov/pubmed/26091670
http://dx.doi.org/10.1186/s12859-015-0630-0
work_keys_str_mv AT srinivasanpadmini ferretasentencebasedliteraturescanningsystem
AT zhangxiaoning ferretasentencebasedliteraturescanningsystem
AT boutenroxane ferretasentencebasedliteraturescanningsystem
AT changcaren ferretasentencebasedliteraturescanningsystem