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A knowledge base for Vitis vinifera functional analysis

Overview of attention for article published in BMC Systems Biology, June 2015
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Title
A knowledge base for Vitis vinifera functional analysis
Published in
BMC Systems Biology, June 2015
DOI 10.1186/1752-0509-9-s3-s5
Pubmed ID
Authors

Alfredo Pulvirenti, Rosalba Giugno, Rosario Distefano, Giuseppe Pigola, Misael Mongiovi, Girolamo Giudice, Vera Vendramin, Alessandro Lombardo, Federica Cattonaro, Alfredo Ferro

Abstract

Vitis vinifera (Grapevine) is the most important fruit species in the modern world. Wine and table grapes sales contribute significantly to the economy of major wine producing countries. The most relevant goals in wine production concern quality and safety. In order to significantly improve the achievement of these objectives and to gain biological knowledge about cultivars, a genomic approach is the most reliable strategy. The recent grapevine genome sequencing offers the opportunity to study the potential roles of genes and microRNAs in fruit maturation and other physiological and pathological processes. Although several systems allowing the analysis of plant genomes have been reported, none of them has been designed specifically for the functional analysis of grapevine genomes of cultivars under environmental stress in connection with microRNA data. Here we introduce a novel knowledge base, called BIOWINE, designed for the functional analysis of Vitis vinifera genomes of cultivars present in Sicily. The system allows the analysis of RNA-seq experiments of two different cultivars, namely Nero d'Avola and Nerello Mascalese. Samples were taken under different climatic conditions of phenological phases, diseases, and geographic locations. The BIOWINE web interface is equipped with data analysis modules for grapevine genomes. In particular users may analyze the current genome assembly together with the RNA-seq data through a customized version of GBrowse. The web interface allows users to perform gene set enrichment by exploiting third-party databases. BIOWINE is a knowledge base implementing a set of bioinformatics tools for the analysis of grapevine genomes. The system aims to increase our understanding of the grapevine varieties and species of Sicilian products focusing on adaptability to different climatic conditions, phenological phases, diseases, and geographic locations.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 1 2%
Unknown 43 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 23%
Researcher 7 16%
Student > Master 6 14%
Student > Bachelor 5 11%
Student > Postgraduate 3 7%
Other 10 23%
Unknown 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 48%
Biochemistry, Genetics and Molecular Biology 5 11%
Computer Science 4 9%
Engineering 2 5%
Unspecified 2 5%
Other 4 9%
Unknown 6 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 December 2015.
All research outputs
#15,169,949
of 25,374,917 outputs
Outputs from BMC Systems Biology
#489
of 1,132 outputs
Outputs of similar age
#137,661
of 281,411 outputs
Outputs of similar age from BMC Systems Biology
#9
of 24 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 53% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 281,411 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.