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SeqVISTA: a graphical tool for sequence feature visualization and comparison.

Overview of attention for article published in BMC Bioinformatics, January 2003
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Title
SeqVISTA: a graphical tool for sequence feature visualization and comparison.
Published in
BMC Bioinformatics, January 2003
Pubmed ID
Authors

Hu, Zhenjun, Frith, Martin, Niu, Tianhua, Weng, Zhiping

Abstract

Many readers will sympathize with the following story. You are viewing a gene sequence in Entrez, and you want to find whether it contains a particular sequence motif. You reach for the browser's "find in page" button, but those darn spaces every 10 bp get in the way. And what if the motif is on the opposite strand? Subsequently, your favorite sequence analysis software informs you that there is an interesting feature at position 13982-14013. By painstakingly counting the 10 bp blocks, you are able to examine the sequence at this location. But now you want to see what other features have been annotated close by, and this information is buried several screenfuls higher up the web page. SeqVISTA presents a holistic, graphical view of features annotated on nucleotide or protein sequences. This interactive tool highlights the residues in the sequence that correspond to features chosen by the user, and allows easy searching for sequence motifs or extraction of particular subsequences. SeqVISTA is able to display results from diverse sequence analysis tools in an integrated fashion, and aims to provide much-needed unity to the bioinformatics resources scattered around the Internet. Our viewer may be launched on a GenBank record by a single click of a button installed in the web browser. SeqVISTA allows insights to be gained by viewing the totality of sequence annotations and predictions, which may be more revealing than the sum of their parts. SeqVISTA runs on any operating system with a Java 1.4 virtual machine. It is freely available to academic users at http://zlab.bu.edu/SeqVISTA.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 3%
Hong Kong 1 3%
Brazil 1 3%
Mexico 1 3%
United States 1 3%
Unknown 29 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 24%
Student > Ph. D. Student 7 21%
Professor 5 15%
Other 3 9%
Student > Master 3 9%
Other 7 21%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 41%
Computer Science 8 24%
Psychology 2 6%
Biochemistry, Genetics and Molecular Biology 2 6%
Chemical Engineering 1 3%
Other 5 15%
Unknown 2 6%