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Visualization in Biology and Medicine

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Scientific Visualization

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

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Abstract

Basic biological research spans a huge range of scales, from studying the genome up to studying populations of people. Biological data is just as expansive. Advances in measuring devices and the public dissemination of large amounts of data has fundamentally changed the way that biologists conduct research and make scientific discoveries. Access to this data has made visualization a key component in almost every biological discovery workflow. In this chapter we focus on visualization in just a few areas of biology and highlight the challenges inherent within each. We present case studies from our own work to illustrate the impact that thoughtfully designed visualization systems can have on complex biological problems and highlight challenges for visualization research in these areas.

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References

  1. Alm, E., Huang, K., Price, M., Koche, R., Keller, K., Dubchak, I., Arkin, A.: The MicrobesOnline web site for comparative genomics. Genome. Res. 15(7), 1015–1022 (2005). doi:10.1101/gr.3844805

  2. Barsky, A., Munzner, T., Gardy, J., Kincaid, R.: Cerebral: Visualizing multiple experimental conditions on a graph with biological context. IEEE Trans. Vis. Comput. Graph. 14(6), 1253–1260 (2008) (Proc. InfoVis 2008). http://doi.ieeecomputersociety.org/10.1109/TVCG.2008.117

  3. Bourqui, R., Westenberg, M.A.: Visualizing temporal dynamics at the genomic and metabolic level. In: IV ’09: Proceedings of the 2009 13th International Conference Information Visualisation, pp. 317–322. IEEE Computer Society, Washington, DC, USA (2009)

    Google Scholar 

  4. Caspi, R., Foerster, H., Fulcher, C., Kaipa, P., Krummenacker, M., Latendresse, M., Paley, S., Rhee, S., Shearer, A., Tissier, C., Walk, T., Zhang, P., Karp, P.: The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res. 36(Database-Issue), 623–631 (2008)

    Google Scholar 

  5. Cedilnik, A., Baumes, J., Ibanez, L., Megason, S., Wylie, B.: Integration of information and volume visualization for analysis of cell lineage and gene expression during embryogenesis. In: Proceedings of SPIE, vol. 6809 (2007)

    Google Scholar 

  6. Clamp, M., Andrews, D., Barker, D., Bevan, P., Cameron, G., Chen, Y., Clark, L., Cox, T., Cuff, J., Curwen, V., Down, T., Durbin, R., Eyras, E., Gilbert, J., Hammond, M., Hubbard, T., Kasprzyk, A., Keefe, D., Lehvaslaiho, H., Iyer, V., Melsopp, C., Mongin, E., Pettett, R., Potter, S., Rust, A., Schmidt, E., Searle, S., Slater, G., Smith, J., Spooner, W., Stabenau, A., Stalker, J., Stupka, E., Ureta-Vidal, A., Vastrik, I., Birney, E.: Ensembl 2002: accommodating comparative genomics. Nucleic Acids Res. 31(1), 38–42 (2003)

    Article  Google Scholar 

  7. Cleveland, W.S., McGill, R.: Graphical perception: theory, experimentation, and application to the development of graphical methods. J. Am. Stat. Assoc. 79(387), 531–554 (1984)

    Article  MathSciNet  Google Scholar 

  8. Darling, A.C., et al.: Mauve: multiple alignment of conserved genomic sequence with rearrangements. Genome Res. 14(7), 1394–1403 (2004)

    Article  Google Scholar 

  9. Eisen, M.B., Spellman, P.T., Brown, P.O., Botstein, D.: Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. 95(25), 14,863–14,868 (1998)

    Google Scholar 

  10. Gehlenborg, N., O’Donoghue, S.I., Baliga, N.S., Goesmann, A., Hibbs, M.A., Kitano, H., Kohlbacher, O., Neuweger, H., Schneider, R., Tenenbaum, D., Gavin, A.C.: Visualization of omics data for systems biology. Nat. Methods 7, S56–S68 (2010)

    Article  Google Scholar 

  11. Goshtasby, A.: 2-D and 3-D Image Registration for Medical, Remote Sensing, and Industrial Applications. Wiley Press, Hoboken (2005)

    Google Scholar 

  12. Hand, A.J., Sun, T., Barber, D.C., Hose, D.R., MacNeil, S.: Automated tracking of migrating cells in phase-contrast video microscopy sequences using image registration. J. Microsc. 234, 62–79 (2009)

    Article  MathSciNet  Google Scholar 

  13. Holten, D.: Hierarchical edge bundles: Visualization of adjacency relations in hierarchical data. IEEE Trans. Vis. Comput. Graph. (Proc. InfoVis 08), 12(5), 741–748 (2006)

    Google Scholar 

  14. Hunt, E., et al.: The visual language of synteny. OMICS J. Integr. Biol. 8(4), 289–305 (2004)

    Article  Google Scholar 

  15. Janoos, F., Nouansengsy, B., Xu, X., Machiraju, R., Wong, S.T.: Classification and uncertainty visualization of dendritic spines from optical microscopy imaging. Comput. Graph. Forum 27(3), 879–886 (2008)

    Article  Google Scholar 

  16. Junker, B.H., Klukas, C., Schreiber, F.: VANTED: a system for advanced data analysis and visualization in the context of biological networks. BMC Bioinf. 7, 109 (2006)

    Article  Google Scholar 

  17. Kanehisa, M., Araki, M., Goto, S., Hattori, M., Hirakawa, M., Itoh, M., Katayama, T., Kawashima, S., Okuda, S., Tokimatsu, T., Yamanishi, Y.: KEGG for linking genomes to life and the environment. Nucleic Acids Res. 36(Database-Issue), 480–484 (2008)

    Google Scholar 

  18. Karp, P., Paley, S., Romero, P.: The pathway tools software. Bioinformatics 18, S225–S232 (2002)

    Article  Google Scholar 

  19. Khairy, K., Keller, P.J.: Reconstructing embryonic development. Genesis 49(7), 488–513 (2011). doi:10.1002/dvg.20698

  20. Kniss, J., Van Uitert, R., Stephens, A., Li, G.S., Tasdizen, T., Hansen, C.: Statistically quantitative volume visualization. In: Visualization, 2005. VIS 05. IEEE, pp. 287–294 (2005)

    Google Scholar 

  21. Kurtz, S., et al.: Versatile and open software for comparing large genomes. Genome Biol. 5(2), R12 (2004)

    Article  Google Scholar 

  22. Leitte, H., Fangerau, J., Lou, X., Höckendorf, B., Lemke, S., Maizel, A., Wittbrodt, J.: Visualization software for 3D video microscopy: a design study. In: M. Meyer, T. Weinkauf (eds.) EuroVis 2012—Short Papers, pp. 73–77. Eurographics Association, Vienna, Austria (2012). doi:10.2312/PE/EuroVisShort/EuroVisShort2012/073-077

  23. Letunic, I., Yamada, T., Kanehisa, M., Bork, P.: iPath: interactive exploration of biochemical pathways and networks. Trends Biochem. Sci. 33(3), 101–103 (2008). doi:10.1016/j.tibs.2008.01.001

  24. Lewis, S., Searle, S., Harris, N., Gibson, M., Iyer, V., Richter, J., Wiel, C., Bayraktaroglu, L., Birney, E., Crosby, M., Kaminker, J., Matthews, B., Prochnik, S., Smith, C., Tupy, J., Rubin, G., Misra, S., Mungall, C., Clamp, M.: Apollo: a sequence annotation editor. Genome Biol. 3(12), research0082.1–0082.14 (2002)

    Google Scholar 

  25. Lou, X., Kaster, F.O., Lindner, M.S., Kausler, B.X., Köthe, U., Höckendorf, B., Wittbrodt, J., Jänicke, H., Hamprecht, F.A.: Deltr: Digital embryo lineage tree reconstructor. In: ISBI 2011: IEEE International Symposium on Biomedical Imaging (2011)

    Google Scholar 

  26. Lucy, L.B.: An iterative technique for the rectification of observed distributions. Astron. J. 79(6), 745–754 (1974)

    Article  Google Scholar 

  27. Meijering, E., Dzyubachyk, O., Smal, I., van Cappellen, W.A.: Tracking in cell and developmental biology. Semin. Cell Dev. Biol. 20(8), 894–902 (2009)

    Article  Google Scholar 

  28. Meyer, M., Munzner, T., Pfister, H.: MizBee: a multiscale synteny browser. IEEE Trans. Vis. Comput. Graph. 15(6), 897–904 (2009) (Proc. InfoVis 2009). http://dx.doi.org/10.1109/TVCG.2009.167

  29. Meyer, M., Wong, B., Styczynski, M., Munzner, T., Pfister, H.: Pathline: A tool for comparative functional genomics. Comput. Graph. Forum 29(3), 1043–1052 (2010) (Proc. EuroVis 10)

    Google Scholar 

  30. Miura, K.: Tracking movement in cell biology. In: Rietdorf, J. (ed.) Microscopy Techniques, Advances in Biochemical Engineering/Biotechnology, vol. 95, pp. 1304–1307. Springer, Berlin (2005)

    Google Scholar 

  31. Mlecnik, B., Scheideler, M., Hackl, H., Hartler, J., Sanchez-Cabo, F., Trajanoski, Z.: PathwayExplorer: web service for visualizing high-throughput expression data on biological pathways. Nucleic Acids Res. 33(Web-Server-Issue), 633–637 (2005)

    Google Scholar 

  32. Olivier, N., Luengo-Oroz, M.A., Duloquin, L., Faure, E., Savy, T., Veilleux, I., Solinas, X., Débarre, D., Bourgine, P., Santos, A., Peyriéras, N., Beaurepaire, E.: Cell lineage reconstruction of early zebrafish embryos using label-free nonlinear microscopy. Science 329(5994), 967–971 (2010)

    Article  Google Scholar 

  33. Pan, X., Stein, L., Brendel, V.: SynBrowse: a synteny browser for comparative sequence analysis. Bioinformatics 21(17), 3461–3468 (2005)

    Article  Google Scholar 

  34. Post, F.H., Vrolijk, B., Hauser, H., Laramee, R.S., Doleisch, H.: The state of the art in flow visualisation: feature extraction and tracking. Comput. Graph. Forum (CGF) 22(4), 775–792 (2003)

    Article  Google Scholar 

  35. Rasko, D., Myers, G., Ravel, J.: Visualization of comparative genomic analyses by BLAST score ratio. BMC Bioinf. 6(1), 2 (2005)

    Article  Google Scholar 

  36. Roberts, J.C.: State of the art: Coordinated & multiple views in exploratory visualization. In: Proceedings of International Conference on Coordinated and Multiple Views in Exploratory Visualization (CMV), pp. 61–71. IEEE Computer Society (2007)

    Google Scholar 

  37. Saad, A., Hamarneh, G., Möller, T.: Exploration and visualization of segmentation uncertainty using shape and appearance prior information. IEEE Trans. Vis. Comput. Graph. 16(6), 1366–1375 (2010)

    Article  Google Scholar 

  38. Saldanha, A.J.: Java Treeview—extensible visualization of microarray data. Bioinformatics 20(17), 3246–3248 (2004). http://dx.doi.org/10.1093/bioinformatics/bth349

  39. Seo, J., Shneiderman, B.: Interactively exploring hierarchical clustering results. Computer 35(7), 80–86 (2002). http://dx.doi.org/10.1109/MC.2002.1016905

  40. Shannon, P., Markiel, A., Ozier, O., Baliga, N., Wang, J., Ramage, D., Amin, N., Schwikowski, B., Ideker, T.: Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13(11), 2498–2504 (2003). doi:10.1101/gr.1239303

  41. Shneiderman, B.: The eyes have it: A task by data type taxonomy for information visualizations. In: Proceedings of IEEE Symposium on Visual Languages (VL), p. 336. IEEE Computer Society, Washington, DC, USA (1996)

    Google Scholar 

  42. Sinha, A., Meller, J.: Cinteny: flexible analysis and visualization of synteny and genome rearrangements in multiple organisms. BMC Bioinf. 8(1), 82 (2007)

    Article  Google Scholar 

  43. Suri, J.S., Wilson, D., Laxminarayan, S. (eds.): Handbook of Biomedical Image Analysis: Volume 2: Segmentation Models Part B. Springer, Berlin (2005)

    Google Scholar 

  44. Szekely, G., Gerig, G.: Model-based segmentation of radiological images. Kuenstliche Intelligenz 14(3), 18–23 (2000)

    Google Scholar 

  45. Szeliski, R.: Image alignment and stitching: a tutorial. Technical Report MSR-TR-2004-92, Microsoft Research (2004)

    Google Scholar 

  46. TIGR (The Institute for Genomic Research): Sybil: Web-based software for comparative genomics (2009). Accessed 1 Mar 2009. http://sybil.sourceforge.net

  47. Timpson, P., McGhee, E.J., Anderson, K.I.: Imaging molecular dynamics in vivo—from cell biology to animal models. J. Cell Sci. 124, 2877–2890 (2011)

    Article  Google Scholar 

  48. Tufte, E.R.: The Visual Display of Quantitative Information, 2 edn. Graphics Press (2001)

    Google Scholar 

  49. Walter, T., Shattuck, D.W., Baldock, R., Bastin, M.E., Carpenter, A.E., Duce, S., Ellenberg, J., Fraser, A., Hamilton, N., Pieper, S., Ragan, M.A., Schneider, J.E., Tomancak, P., Hériché, J.K.: Visualization of image data from cells to organisms. In: Visualizing Biological Data, vol. 7, pp. S26–S41. Nature Methods (2010)

    Google Scholar 

  50. Ware, C.: Information visualization: perception for design. Morgan Kaufmann , Burlington (2000) (Chapter 4)

    Google Scholar 

  51. Weber, G.H., Luengo, C.L.H., Keränen, S.V.E., Dillard, S.E., Ju, D., Sudar, D., Hamann, B.: Visualization for validation and improvement of three-dimensional segmentation algorithms. In: Data Visualization 2005 (Proceedings of the EUROGRAPHICS—IEEE VGTC Symposium on Visualization 2005). Eurographics Association (2005)

    Google Scholar 

  52. Weinstein, J.N.: A postgenomic visual icon. Science 319(5871), 1772–1773 (2008). doi:10.1126/science.1151888

  53. Wilkinson, L., Friendly, M.: The history of the cluster heat map. Am. Stat. 63(2), 179–184 (2009)

    Article  MathSciNet  Google Scholar 

  54. Wong, B.: Points of view: color coding. Nat Methods 7(8), 573 (2010)

    Article  Google Scholar 

  55. Wylie, B., Baumes, J.: A unified toolkit for information and scientific visualization. Visual Data Analytics (2009)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Im Neuenheimer Feld 368, 69120, Heidelberg, Germany

    Heike Leitte

  2. School of Computing, University of Utah, 72 S. Central Campus Dr, Salt Lake City, UT, 84112, USA

    Miriah Meyer

Authors
  1. Heike Leitte
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  2. Miriah Meyer
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Corresponding author

Correspondence to Heike Leitte .

Editor information

Editors and Affiliations

  1. School of Computing Scientific Computing and Imaging Institu, University of Utah, Salt Lake City, Utah, USA

    Charles D. Hansen

  2. e-Research Centre, University of Oxford, Oxford, United Kingdom

    Min Chen

  3. School of Computing Scientific Computing and Imaging Institu, University of Utah, Salt Lake City, Utah, USA

    Christopher R. Johnson

  4. Department of Computer Science, Stony Brook University, New York, New York, USA

    Arie E. Kaufman

  5. Fachbereich Informatik, Technische Universität Kaiserslautern, Kaiserslautern, Germany

    Hans Hagen

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Leitte, H., Meyer, M. (2014). Visualization in Biology and Medicine. In: Hansen, C., Chen, M., Johnson, C., Kaufman, A., Hagen, H. (eds) Scientific Visualization. Mathematics and Visualization. Springer, London. https://doi.org/10.1007/978-1-4471-6497-5_22

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