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KBWS: an EMBOSS associated package for accessing bioinformatics web services

Overview of attention for article published in Source Code for Biology and Medicine, April 2011
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Title
KBWS: an EMBOSS associated package for accessing bioinformatics web services
Published in
Source Code for Biology and Medicine, April 2011
DOI 10.1186/1751-0473-6-8
Pubmed ID
Authors

Kazuki Oshita, Kazuharu Arakawa, Masaru Tomita

Abstract

The availability of bioinformatics web-based services is rapidly proliferating, for their interoperability and ease of use. The next challenge is in the integration of these services in the form of workflows, and several projects are already underway, standardizing the syntax, semantics, and user interfaces. In order to deploy the advantages of web services with locally installed tools, here we describe a collection of proxy client tools for 42 major bioinformatics web services in the form of European Molecular Biology Open Software Suite (EMBOSS) UNIX command-line tools. EMBOSS provides sophisticated means for discoverability and interoperability for hundreds of tools, and our package, named the Keio Bioinformatics Web Service (KBWS), adds functionalities of local and multiple alignment of sequences, phylogenetic analyses, and prediction of cellular localization of proteins and RNA secondary structures. This software implemented in C is available under GPL from http://www.g-language.org/kbws/ and GitHub repository http://github.com/cory-ko/KBWS. Users can utilize the SOAP services implemented in Perl directly via WSDL file at http://soap.g-language.org/kbws.wsdl (RPC Encoded) and http://soap.g-language.org/kbws_dl.wsdl (Document/literal).

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 5%
Japan 1 2%
Netherlands 1 2%
United States 1 2%
Unknown 38 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 23%
Student > Bachelor 7 16%
Professor > Associate Professor 7 16%
Student > Master 4 9%
Student > Ph. D. Student 4 9%
Other 8 19%
Unknown 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 53%
Computer Science 6 14%
Biochemistry, Genetics and Molecular Biology 4 9%
Medicine and Dentistry 4 9%
Engineering 2 5%
Other 0 0%
Unknown 4 9%
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 03 December 2011.
All research outputs
#14,722,660
of 22,659,164 outputs
Outputs from Source Code for Biology and Medicine
#82
of 127 outputs
Outputs of similar age
#83,527
of 110,029 outputs
Outputs of similar age from Source Code for Biology and Medicine
#2
of 3 outputs
Altmetric has tracked 22,659,164 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
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 110,029 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.