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GTB – an online genome tolerance browser

Overview of attention for article published in BMC Bioinformatics, January 2017
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Title
GTB – an online genome tolerance browser
Published in
BMC Bioinformatics, January 2017
DOI 10.1186/s12859-016-1436-4
Pubmed ID
Authors

Hashem A. Shihab, Mark F. Rogers, Michael Ferlaino, Colin Campbell, Tom R. Gaunt

Abstract

Accurate methods capable of predicting the impact of single nucleotide variants (SNVs) are assuming ever increasing importance. There exists a plethora of in silico algorithms designed to help identify and prioritize SNVs across the human genome for further investigation. However, no tool exists to visualize the predicted tolerance of the genome to mutation, or the similarities between these methods. We present the Genome Tolerance Browser (GTB, http://gtb.biocompute.org.uk ): an online genome browser for visualizing the predicted tolerance of the genome to mutation. The server summarizes several in silico prediction algorithms and conservation scores: including 13 genome-wide prediction algorithms and conservation scores, 12 non-synonymous prediction algorithms and four cancer-specific algorithms. The GTB enables users to visualize the similarities and differences between several prediction algorithms and to upload their own data as additional tracks; thereby facilitating the rapid identification of potential regions of interest.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 5%
Unknown 18 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 37%
Student > Bachelor 3 16%
Student > Ph. D. Student 3 16%
Professor 2 11%
Student > Master 1 5%
Other 1 5%
Unknown 2 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 37%
Agricultural and Biological Sciences 4 21%
Computer Science 3 16%
Nursing and Health Professions 1 5%
Sports and Recreations 1 5%
Other 0 0%
Unknown 3 16%