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Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future

Overview of attention for article published in Giga Science, August 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

twitter
25 X users
patent
1 patent
peer_reviews
1 peer review site
facebook
1 Facebook page
wikipedia
1 Wikipedia page
googleplus
7 Google+ users

Citations

dimensions_citation
92 Dimensions

Readers on

mendeley
287 Mendeley
citeulike
4 CiteULike
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Title
Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future
Published in
Giga Science, August 2015
DOI 10.1186/s13742-015-0077-2
Pubmed ID
Authors

Georgios A. Pavlopoulos, Dimitris Malliarakis, Nikolas Papanikolaou, Theodosis Theodosiou, Anton J. Enright, Ioannis Iliopoulos

Abstract

"Α picture is worth a thousand words." This widely used adage sums up in a few words the notion that a successful visual representation of a concept should enable easy and rapid absorption of large amounts of information. Although, in general, the notion of capturing complex ideas using images is very appealing, would 1000 words be enough to describe the unknown in a research field such as the life sciences? Life sciences is one of the biggest generators of enormous datasets, mainly as a result of recent and rapid technological advances; their complexity can make these datasets incomprehensible without effective visualization methods. Here we discuss the past, present and future of genomic and systems biology visualization. We briefly comment on many visualization and analysis tools and the purposes that they serve. We focus on the latest libraries and programming languages that enable more effective, efficient and faster approaches for visualizing biological concepts, and also comment on the future human-computer interaction trends that would enable for enhancing visualization further.

X Demographics

X Demographics

The data shown below were collected from the profiles of 25 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 287 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 1%
United Kingdom 3 1%
France 2 <1%
Spain 2 <1%
Colombia 1 <1%
Czechia 1 <1%
India 1 <1%
Brazil 1 <1%
Singapore 1 <1%
Other 3 1%
Unknown 268 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 70 24%
Student > Ph. D. Student 55 19%
Student > Master 54 19%
Student > Bachelor 27 9%
Student > Postgraduate 13 5%
Other 38 13%
Unknown 30 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 99 34%
Biochemistry, Genetics and Molecular Biology 56 20%
Computer Science 44 15%
Medicine and Dentistry 12 4%
Engineering 7 2%
Other 36 13%
Unknown 33 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 30. 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 15 July 2022.
All research outputs
#1,314,411
of 25,373,627 outputs
Outputs from Giga Science
#215
of 1,167 outputs
Outputs of similar age
#17,407
of 279,406 outputs
Outputs of similar age from Giga Science
#4
of 16 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,167 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.8. This one has done well, scoring higher than 81% 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 279,406 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.