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A web-oriented software for the optimization of pooled experiments in NGS for detection of rare mutations

Overview of attention for article published in BMC Research Notes, February 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)

Mentioned by

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1 tweeter
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1 Google+ user

Citations

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3 Dimensions

Readers on

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5 Mendeley
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Title
A web-oriented software for the optimization of pooled experiments in NGS for detection of rare mutations
Published in
BMC Research Notes, February 2016
DOI 10.1186/s13104-016-1889-6
Pubmed ID
Authors

Daniela Evangelista, Antonio Zuccaro, Algirdas Lančinskas, Julius Žilinskas, Mario R. Guarracino

Abstract

The cost per patient of next generation sequencing for detection of rare mutations may be significantly reduced using pooled experiments. Recently, some techniques have been proposed for the planning of pooled experiments and for the optimal allocation of patients into pools. However, the lack of a user friendly resource for planning the design of pooled experiments forces the scientists to do frequent, complex and long computations. OPENDoRM is a powerful collection of novel mathematical algorithms usable via an intuitive graphical user interface. It enables researchers to speed up the planning of their routine experiments, as well as, to support scientists without specific bioinformatics expertises. Users can automatically carry out analysis in terms of costs associated with the optimal allocation of patients in pools. They are also able to choose between three distinct pooling mathematical methods, each of which also suggests the optimal configuration for the submitted experiment. Importantly, in order to keep track of the performed experiments, users can save and export the results of their experiments in standard tabular and charts contents. OPENDoRM is a freely available web-oriented application for the planning of pooled NGS experiments, available at: http://www-labgtp.na.icar.cnr.it/OPENDoRM. Its easy and intuitive graphical user interface enables researchers to plan theirs experiments using novel algorithms, and to interactively visualize the results.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 20%
Professor 1 20%
Student > Ph. D. Student 1 20%
Researcher 1 20%
Student > Postgraduate 1 20%
Other 0 0%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 40%
Computer Science 2 40%
Biochemistry, Genetics and Molecular Biology 1 20%

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 24 February 2016.
All research outputs
#7,314,169
of 12,680,054 outputs
Outputs from BMC Research Notes
#1,197
of 2,852 outputs
Outputs of similar age
#121,679
of 266,746 outputs
Outputs of similar age from BMC Research Notes
#1
of 2 outputs
Altmetric has tracked 12,680,054 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,852 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 54% 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 266,746 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them