DocumentCode :
229075
Title :
Bacterial gene neighborhood investigation environment: A large-scale genome visualization for big displays
Author :
Aurisano, Jillian ; Reda, Khairi ; Johnson, A. ; Leigh, J.
Author_Institution :
Electron. Visualization Lab., Univ. of Illinois at Chicago, Chicago, IL, USA
fYear :
2014
fDate :
9-10 Nov. 2014
Firstpage :
103
Lastpage :
104
Abstract :
Improvements in genome sequencing technology over the past decade have driven down sequencing costs faster than Moore´s Law producing a genome sequencing boom [9]. Accelerated rates of complete genome sequence production are particularly evident in bacterial genomics, where small genome sizes enable rapid and inexpensive sequencing. These large volumes of complete genome sequences have given researchers a new approach to the longstanding challenge of identifying and characterizing novel bacterial genes: comparative gene neighborhood analysis. Due to unique properties in bacterial genome organization, researchers believe that it is possible to generate hypotheses around the function and pathway membership of novel genes by examining the neighborhood around gene orthologs, or genes with highly similar sequences. Visual approaches to this problem are necessary, since subtle patterns and relationships can be missed through automated approaches, but current comparative gene neighborhood visualizations are only designed to accomodate comparisons across 2-9 genomes in a single view ( [8, 4, 6, 5, 2, 7, 3]).
Keywords :
biology computing; data visualisation; genetic engineering; microorganisms; bacterial gene neighborhood investigation environment; bacterial genes; bacterial genome organization; bacterial genomics; big displays; comparative gene neighborhood analysis; gene orthologs; genome sequence production; genome sequencing technology; genome visualization; pathway membership; sequencing costs; visual approaches; Bioinformatics; Data visualization; Genomics; Image color analysis; Microorganisms; Sequential analysis; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Large Data Analysis and Visualization (LDAV), 2014 IEEE 4th Symposium on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/LDAV.2014.7013210
Filename :
7013210
Link To Document :
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