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InteGO2: a web tool for measuring and visualizing gene semantic similarities using Gene Ontology

Overview of attention for article published in BMC Genomics, August 2016
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Title
InteGO2: a web tool for measuring and visualizing gene semantic similarities using Gene Ontology
Published in
BMC Genomics, August 2016
DOI 10.1186/s12864-016-2828-6
Pubmed ID
Authors

Jiajie Peng, Hongxiang Li, Yongzhuang Liu, Liran Juan, Qinghua Jiang, Yadong Wang, Jin Chen

Abstract

The Gene Ontology (GO) has been used in high-throughput omics research as a major bioinformatics resource. The hierarchical structure of GO provides users a convenient platform for biological information abstraction and hypothesis testing. Computational methods have been developed to identify functionally similar genes. However, none of the existing measurements take into account all the rich information in GO. Similarly, using these existing methods, web-based applications have been constructed to compute gene functional similarities, and to provide pure text-based outputs. Without a graphical visualization interface, it is difficult for result interpretation. We present InteGO2, a web tool that allows researchers to calculate the GO-based gene semantic similarities using seven widely used GO-based similarity measurements. Also, we provide an integrative measurement that synergistically integrates all the individual measurements to improve the overall performance. Using HTML5 and cytoscape.js, we provide a graphical interface in InteGO2 to visualize the resulting gene functional association networks. InteGO2 is an easy-to-use HTML5 based web tool. With it, researchers can measure gene or gene product functional similarity conveniently, and visualize the network of functional interactions in a graphical interface. InteGO2 can be accessed via http://mlg.hit.edu.cn:8089/ .

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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 24%
Researcher 3 12%
Student > Bachelor 3 12%
Student > Postgraduate 2 8%
Other 2 8%
Other 3 12%
Unknown 6 24%
Readers by discipline Count As %
Computer Science 6 24%
Agricultural and Biological Sciences 6 24%
Biochemistry, Genetics and Molecular Biology 4 16%
Psychology 1 4%
Engineering 1 4%
Other 0 0%
Unknown 7 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 September 2016.
All research outputs
#6,364,432
of 8,386,076 outputs
Outputs from BMC Genomics
#4,643
of 5,931 outputs
Outputs of similar age
#177,255
of 251,910 outputs
Outputs of similar age from BMC Genomics
#223
of 318 outputs
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We're also able to compare this research output to 318 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.