Revised abstract: (remove current and replace with this) Cutting-edge biological and bioinformatics research seeks a systems perspective through the analysis of multiple types of high-throughput and other experimental data for the same
sample. Systems-level analysis requires the integration and fusion of such data, typically through advanced statistics and mathematics. Visualization is a complementary com-putational approach that supports integration and
analysis of complex data or its derivatives. We present a bioinformatics visualization prototype, Juxter, which depicts categorical information derived from or assigned to these diverse data for the purpose of comparing patterns across
categorizations. The visualization allows users to easily discern correlated and anomalous patterns in the data. These patterns, which might not be detected automatically by algorithms, may reveal valuable information leading to
insight and discovery. We describe the visualization and interaction capabilities and demonstrate its utility in a new field, metagenomics, which combines molecular biology and genetics to identify and characterize genetic material from
multi-species microbial samples.
Revised: May 19, 2011 |
Published: August 10, 2005
Citation
Havre S.L., B.M. Webb-Robertson, A. Shah, C. Posse, B. Gopalan, and F.J. Brockman. 2005.Bioinformatic Insights from Metagenomics through Visualization. In Proceedings of the IEEE Computational Systems Bioinformatics Conference (CSB 2005). August 8-11, 2005, 341-350. Los Alamitos, California:IEEE Computer Society.PNNL-SA-44583.doi:10.1109/CSB.2005.19