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2015 ; 16
(1
): 198
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Ferret: a sentence-based literature scanning system
#MMPMID26091670
Srinivasan P
; Zhang XN
; Bouten R
; Chang C
BMC Bioinformatics
2015[Jun]; 16
(1
): 198
PMID26091670
show ga
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.
|*Databases, Bibliographic
[MESH]
|*PubMed
[MESH]
|*Software
[MESH]
|Arabidopsis Proteins/*genetics
[MESH]
|Arabidopsis/*genetics
[MESH]
|Ethylenes/metabolism
[MESH]
|Flowers/chemistry
[MESH]
|Information Storage and Retrieval/*methods
[MESH]
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