TY - GEN
T1 - Systems support for remote visualization of genomics applications over wide area networks
AU - Bongo, Lars Ailo
AU - Wallace, Grant
AU - Larsen, Tore
AU - Li, Kai
AU - Troyanskaya, Olga G.
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - Microarray experiments can provide molecular-level insight into a variety of biological processes, from yeast cell cycle to tumorogenesis. However, analysis of both genomic and protein microarray data requires interactive collaborative investigation by biology and bioinformatics researchers. To assist collaborative analysis, remote collaboration tools for integrative analysis and visualization of microarray data are necessary. Such tools should: (i) provide fast response times when used with visualizationintensive genomics applications over a low-bandwidth wide area network, (ii) eliminate transfer of large and often sensitive datasets, (iii) work with any analysis software, and (iv) be platform-independent. Existing visualization systems do not satisfy all requirements. We have developed a remote visualization system called Varg that extends the platform-independent remote desktop system VNC with a novel global compression method. Our evaluations show that the Varg system can support interactive visualization-intensive genomic applications in a remote environment by reducing bandwidth requirements from 30:1 to 289:1.
AB - Microarray experiments can provide molecular-level insight into a variety of biological processes, from yeast cell cycle to tumorogenesis. However, analysis of both genomic and protein microarray data requires interactive collaborative investigation by biology and bioinformatics researchers. To assist collaborative analysis, remote collaboration tools for integrative analysis and visualization of microarray data are necessary. Such tools should: (i) provide fast response times when used with visualizationintensive genomics applications over a low-bandwidth wide area network, (ii) eliminate transfer of large and often sensitive datasets, (iii) work with any analysis software, and (iv) be platform-independent. Existing visualization systems do not satisfy all requirements. We have developed a remote visualization system called Varg that extends the platform-independent remote desktop system VNC with a novel global compression method. Our evaluations show that the Varg system can support interactive visualization-intensive genomic applications in a remote environment by reducing bandwidth requirements from 30:1 to 289:1.
KW - Compression
KW - Genomics collaboration
KW - Rabin fingerprints
KW - Remote visualization
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U2 - 10.1007/978-3-540-69968-2_12
DO - 10.1007/978-3-540-69968-2_12
M3 - Conference contribution
AN - SCOPUS:34547433774
SN - 3540698418
SN - 9783540698418
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 157
EP - 174
BT - Distributed, High-Performance and Grid Computing in Computational Biology International Workshop, GCCB 2006, Proceedings
PB - Springer Verlag
T2 - Distributed, High-Performance and Grid Computing in Computational Biology International Workshop, GCCB 2006
Y2 - 21 January 2007 through 21 January 2007
ER -