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ANDSystem: an Associative Network Discovery System for automated literature mining in the field of biology.

Overview of attention for article published in BMC Systems Biology, April 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
32 Mendeley
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Title
ANDSystem: an Associative Network Discovery System for automated literature mining in the field of biology.
Published in
BMC Systems Biology, April 2015
DOI 10.1186/1752-0509-9-s2-s2
Pubmed ID
Authors

Vladimir A Ivanisenko, Olga V Saik, Nikita V Ivanisenko, Evgeny S Tiys, Timofey V Ivanisenko, Pavel S Demenkov, Nikolay A Kolchanov

Abstract

Sufficient knowledge of molecular and genetic interactions, which comprise the entire basis of the functioning of living systems, is one of the necessary requirements for successfully answering almost any research question in the field of biology and medicine. To date, more than 24 million scientific papers can be found in PubMed, with many of them containing descriptions of a wide range of biological processes. The analysis of such tremendous amounts of data requires the use of automated text-mining approaches. Although a handful of tools have recently been developed to meet this need, none of them provide error-free extraction of highly detailed information. The ANDSystem package was developed for the reconstruction and analysis of molecular genetic networks based on an automated text-mining technique. It provides a detailed description of the various types of interactions between genes, proteins, microRNA's, metabolites, cellular components, pathways and diseases, taking into account the specificity of cell lines and organisms. Although the accuracy of ANDSystem is comparable to other well known text-mining tools, such as Pathway Studio and STRING, it outperforms them in having the ability to identify an increased number of interaction types. The use of ANDSystem, in combination with Pathway Studio and STRING, can improve the quality of the automated reconstruction of molecular and genetic networks. ANDSystem should provide a useful tool for researchers working in a number of different fields, including biology, biotechnology, pharmacology and medicine.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 3%
United States 1 3%
Singapore 1 3%
Unknown 29 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 31%
Student > Master 6 19%
Student > Ph. D. Student 5 16%
Other 4 13%
Professor 2 6%
Other 5 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 28%
Biochemistry, Genetics and Molecular Biology 8 25%
Unspecified 5 16%
Medicine and Dentistry 3 9%
Computer Science 3 9%
Other 4 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 04 February 2016.
All research outputs
#7,330,732
of 13,889,642 outputs
Outputs from BMC Systems Biology
#383
of 1,089 outputs
Outputs of similar age
#87,684
of 225,766 outputs
Outputs of similar age from BMC Systems Biology
#2
of 2 outputs
Altmetric has tracked 13,889,642 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,089 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 62% 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 225,766 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 60% 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.