Visual exploration of microbial populations

IEEE Symposium on Biological Data Visualization 2011, BioVis 2011 - Proceedings

Volumn , Issue , 2011, Pages 127-134

  Fernstad, Sara Johansson ^a   Johansson, Jimmy ^a   Adams, Suzi ^b   Shaw, Jane ^b   Taylor, David ^b  

^a LINKÖPING UNIVERSITY   (Sweden)

^b UNILEVER RESEARCH   (United Kingdom)

Author keywords

H.4.m Information Systems Applications Miscellaneous; J.3 Life and Medical Science Biology and genetics

Indexed keywords

ANALYSIS METHOD; DATA SETS; DATA SUBSETS; DIMENSIONALITY REDUCTION; END USERS; HIGH DIMENSIONAL DATA; INFORMATION SYSTEMS APPLICATION; INFORMATION VISUALIZATION; INTERACTIVE ANALYSIS; INTERACTIVE ENVIRONMENTS; INTERACTIVE SYSTEM; INTERACTIVITY; LIFE AND MEDICAL SCIENCE; MICROBIAL POPULATIONS; RESEARCH AREAS; VISUAL ANALYSIS; VISUAL EXPLORATION;

CLUSTERING ALGORITHMS; DATA VISUALIZATION; ECOLOGY; FEEDBACK; INFORMATION SYSTEMS; VISUALIZATION;

POPULATION STATISTICS;

EID: 84255188301     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BioVis.2011.6094057     Document Type: Conference Paper

References (39)

1. S. Adams, A. Scott, C. Alonso, D. Taylor, J. Shaw, A. Smith, P. Helme, C. Quince, and I. L. Chapple. Examining oral bacterial populations in health and gingivitis using 454-pyrosequencing. Presented at the IADR General Session, San Diego, California, 2011.
2. S. E. Adams, A. M. Lloyd, M. G. Brading, T. F. Cox, D. Taylor, and C. Quince. Measurement of bacterial diversity using 454-sequencing and oral microarray (HOMIM). Presented at the IADR General Session, Barcelona, Spain, 2010.
3. C. Ahlberg. Spotfire: an information exploration environment. ACM SIGMOD Record, 25(4):25-29, 1996.
4. G. Albuquerque, M. Eisemann, D. J. Lehmann, H. Theisel, and M. Magnor. Improving the visual analysis of high-dimensional datasets using quality measures. In Proceedings of IEEE Symposium on Visual Analytics Science and Technology, pages 19-26. IEEE, October 2010.
5. A. Barsky, T. Munzner, J. Gardy, and R. Kincaid. Cerebral: Visualizing multiple experimental conditions on a graph with biological context. IEEE Transactions on Visualization and Computer Graphics, 14(6):1253-1260, 2008.
6. R. A. Becker and W. S. Cleveland. Brushing scatterplots. Technometrics, 29(2):127-142, May 1987.
7. J. G. Caporaso, J. Kuczynski, J. Stombaugh, K. Bittinger, F. D. Bushman, E. K. Costello, N. Fierer, A. G. Pea, J. K. Goodrich, J. I. Gordon, G. A. Huttley, S. T. Kelley, D. Knights, J. E. Koenig, R. E. Ley, C. A. Lozupone, D. McDonald, B. D. Muegge, M. Pirrung, J. Reeder, J. R. Sevinsky, P. J. Turnbaugh,W. A.Walters, J.Widmann, T. Yatsunenko, J. Zaneveld, and R. Knight. QIIME allows analysis of high-throughput community sequencing data. Nature Methods, 7(5):335-336, 2010.
8. J. R. Cole, Q. Wang, E. Cardenas, J. Fish, B. Chai, R. J. Farris, A. S. Kulam-Syed-Mohideen, D. M. McGarrell, T. Marsh, G. M. Garrity, and J. M. Tiedje. The ribosomal database project: improved alignments and new tools for rRNA analysis. Nucleic Acids Research, 37(Suppl. 1):D141-D145, 2009.
9. T. Cox. Introduction to Multivariate Analysis. Hodder Arnold, 2005.
10. J. Dietzsch, J. Heinrich, K. Nieselt, and D. Bartz. Spray: A visual analytics approach for gene expression data. In Proceedings of IEEE Symposium on Viusal Analystics Science and Technology, pages 179-186. IEEE, October 2009.
11. M. B. Eisen, P. T. Spellman, P. O. Brown, and D. Botstein. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA, 95(25):14863-14868, 1998.
12. N. Gehlenborg, S. I. O'Donoghue, N. S. Baliga, A. Goesmann, M. A. Hibbs, H. Kitano, O. Kohlbacher, H. Neuweger, R. Schneider, D. Tenenbaum, and A.-C. Gavin. Visualization of omics data for systems biology. Nature Methods, Visualizing Biological Data, 7(3s):56-68, March 2010.
13. Genespring. http://www.genomics.agilent.com/.
14. D. E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley, 1989.
15. S. Grimshaw, P. Helme, C. Quince, J. Shaw, A. Smith, and D. Taylor. The axillary microbiome: Defining the microbial ecology of the human underarm across time and space. Presented at ISME-13 Stewards of a changing planet, Seattle, WA, USA, 2010.
16. H. Hochheiser, E. H. Baehrecke, S. M. Mount, and B. Shneiderman. Dynamic querying for pattern identification in microarray and genomic data. In Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3, pages 453-456. IEEE Computer Society, 2003.
17. Z. Hu, J. Mellor, J. Wu, and C. DeLisi. VisANT: an online visualization and analysis tool for biological interaction data. BMC Bioinformatics, 5(1):17, 2004.
18. IEEE. 1st IEEE Symposium on Biological Data Visualization, Providence, RI, USA, October 2011.
19. S. Ingram, T. Munzner, V. Irvine, M. Tory, S. Bergner, and T. Möller. Dimstiller: Workflows for dimensional analysis and reduction. In Proceedings of IEEE Symposium on Visual Analytics Science and Technology, pages 3-10. IEEE, October 2010.
20. A. Inselberg. The plane with parallel coordinates. The Visual Computer, 1(4):69-91, 1985.
21. S. Johansson and J. Johansson. Interactive dimensionality reduction through user-defined combinations of quality metrics. IEEE Transactions on Visualization and Computer Graphics, 15(6):993-1000, 2009.
22. B. Kim, B. Lee, S. Knoblach, E. Hoffman, and J. Seo. Geneshelf: A web-based visual interface for large gene expression time-series data repositories. IEEE Transactions on Visualization and Computer Graphics, 15(6):905-912, 2009.
23. T. Kohonen. The self-organizing map. Neurocomputing, 21(1-3):1-6, 1998.
24. R. E. Ley, C. A., Lozupone, M. Hamady, R. Knight, and J. I. Gordon. Worlds within worlds: evolution of the vertebrate gut microbiota. Nature Reviews Microbiology, 6(10):766-788, 2008.
25. C. Lozupone and R. Knight. UniFrac: a new phylogenetic method for comparing microbial communities. Applied and Environmental Microbiology, 71(12):8228-8235, 2005.
26. A. E. Magurran. Measuring Biological Diversity. Blackwell Science Ltd, 2004.
27. Visualizing biological data. Nature Methods, 7(3s), March 2010.
28. S. O'Donoghue, B. Wong, J. Procter, and L. Hunter, editors. Workshop on Visualizing Biological Data, Broad Institute, Cambridge, MA, USA, March 2011.
29. G. Pavlopoulos, A.-L. Wegener, and R. Schneider. A survey of visualization tools for biological network analysis. BioData Mining, 1(1):12, 2008.
30. R. Rao and S. K. Card. The table lens: merging graphical and symbolic representations in an interactive focus + context visualization for tabular information. In Proceedings of the SIGCHI conference on Human factors in computing systems: celebrating interdependence, pages 318-322. ACM, 1994.
31. P. Saraiya, C. North, and K. Duca. An evaluation of microarray visualization tools for biological insight. In Proceedings of IEEE Symposium on Information Visualization, pages 1-8. IEEE, October 2004.
32. P. Saraiya, C. North, and K. Duca. Visualizing biological pathways: Requirements analysis, systems evaluation and research agenda. Information Visualization, 4(3):191-205, 2005.
33. J. Seo and B. Shneiderman. Interactively exploring hierarchical clustering results. IEEE Computer, 35(7):80-86, 2002.
34. P. Shannon, A. Markiel, O. Ozier, N. S. Baliga, J. T. Wang, D. Ramage, N. Amin, B. Schwikowski, and T. Ideker. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res., 13(11):2498-2504, 2003.
35. W. Shannon. Personal Communication.
36. M. Sips, B. Neubert, J. P. Lewis, and P. Hanrahan. Selecting good views of high-dimensional data using class consistency. Computer Graphics Forum, 28(3):831-838, 2009.
37. M. Suderman and M. Hallet. Tools for visually exploring biological networks. Bioinformatics, 23(20):2651-2659, 2007.
38. A. Tatu, G. Albuquerque, M. Eisemann, P. Bak, H. Theisel, M. Magnor, and D. Keim. Automated analytical methods to support visual exploration of high-dimensional data. IEEE Transactions on Visualization and Computer Graphics, 17(5):584-597, May 2011.
39. J. R. White, N. Nagarajan, and M. Pop. Statistical methods for detecting differentially abundant features in clinical metagenomic samples. PLoS Computational Biology, 5(4):e1000352, 2009.