Abstract
We present a method to generate glyphs which convey complex information in graphical form. A glyph has a linear geometry which is specified using geometric operations, each represented by characters nested in a string. This format allows several glyph strings to be concatenated, resulting in more complex geometries. We explore automatic generation of a large number of glyphs using a genetic algorithm. To measure the visual distinctness between two glyph geometries, we use the iterative closest point algorithm. We apply these methods to create two different types of representations for biological proteins, transforming the rich data describing their various characteristics into graphical form. The representations are automatically built from a finite set of glyphs, which have been created manually or using the genetic algorithm.
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References
Alt, H., Guibas, L.J.: Discrete Geometric Shapes: Matching, Interpolation, and Approximation. In: Sack, J.R., Urrutia, J. (eds.) Handbook of Computational Geometry, pp. 121–153. Elsevier Science Publishers, Amsterdam (1999)
Alfarano, C., Andrade, C.E., Anthony, K., Bahroos, N., Bajec, M.: The Biomolecular Interaction Network Database and related tools 2005 update. Nucleic Acids Res. 33(Database Issue), G418–G424 (2005)
Bateman, A., Birney, E., Cerruti, L., Durbin, R., Etwiller, L., Eddy, S.R., Griffiths-Jones, S., Howe, K.L., Marshall, M., Sonnhammer, E.L.L.: The Pfam Protein Families Database. Nucleic Acids Research 30(1), 276–280 (2002)
Battiato, S., Gallo, G., Nicotra, S.: Glyph Representation of Directional Texture Properties. Journal of WSCG 10(1-3), 48–54 (2002)
Bergman, L.D., Richardson, J.S., Richardson, D.C., Brooks, J.F.P.: VIEW - an exploratory molecular visualization system with user-definable interaction sequences. In: Proceedings of SIGGRAPH, vol. 71, pp. 117–126 (1993)
Besl, P.J., MacKay, N.D.: A Method for Registration of 3-D Shapes. IEEE Transactions on Pattern Analysis and Machine Inteligence 14, 239–256 (1992)
Fasulo, D.: An Analysis of Recent Work on Clustering Algorithms. In: Department of Computer Science & Engineering, University of Washington (1999)
The Gene Ontology Consortium: Gene Ontology: tool for the unification of biology. Nature Genetics 25, 25–29 (2000)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading (1989)
Hoffmann, C.M.: Geometric and solid modeling: an introduction. Morgan Kaufmann Publishers Inc., San Francisco (1989)
Jain, A.K., Dubes, R.C.: Algorithms for clustering data. Prentice-Hall, Englewood Cliffs (1988)
Lindenmayer, A.: Mathematical models for cellular interaction in development, Parts I and II. Journal of Theoretical Biology 18, 280–315 (1968)
Marchler-Bauer, A., Panchenko, A.R., Shoemaker, B.A., Thiessen, P.A., Geer, L.Y., Bryant, S.H.: CDD: a database of conserved domain alignments with links to domain three-dimensional structure. Nucleic Acids Research 30(1), 281–283 (2002)
Martz, E.: 3D Molecular Visualization with Protein Explorer. In: Krawetz, S.A., Womble, D.D. (eds.) Introduction to Bioinformatics, pp. 565–586. Humana Press, Totowa (2003)
Michalickova, K., Bader, G.D., Dumontier, M., Lieu, H., Betel, D., Isserlin, R., Hogue, C.W.: Seqhound: biological sequence and structure database as a platform for bioinformatics research. BMC Bioinformatics 3(1), 32–45 (2002)
Murzin, A.G., Brenner, S.E., Hubbard, T., Chothia, C.: SCOP: a structural classification of proteins database for the investigation of sequences and structures. J. Mol. Biol. 247, 536–540 (1995)
Prusinkiewicz, P., Hanan, J.: Visualization of botanical structures and processes using parametric L-systems. In: Scientific Visualization and Graphics Simulation, pp. 183–201. J. Wiley & Sons, Chichester (1990)
Renner, G., Ekárt, A.: Genetic algorithms in computer aided design. Computer-Aided Design 35(8), 709–726 (2003)
Ribarsky, W., Ayers, E., Eble, J., Mukherjea, S.: Glyphmaker: Creating customized visualizations of complex data. IEEE Computer 27(7), 57–64 (1994)
Rose, S.J., Wong, P.C.: DriftWeed: a visual metaphor for interactive analysis of multivariate data. In: Visual Data Exploration and Analysis VII (Proceedings of SPIE), vol. 3960, pp. 114–121 (2000)
Schultz, J., Copley, R.R., Doerks, T., Ponting, C.P., Bork, P.: SMART: A Web-based tool for the study of genetically mobile domains. Nucleic Acids Res. 28, 231–234 (2000)
Sims, K.: Evolving Virtual Creatures. Computer Graphics, 15–22 (1994)
Voorhees, E.M.: Implementing Agglomerative Hierarchic Clustering Algorithms for use in Document Retrieval. Information Processing & Management 22(6), 465–476 (1986)
Wang, Y., Geer, L.Y., Chappey, C., Kans, J.A., Bryant, S.H.: Cn3D: sequence and structure views for Entrez. Trends Biochem Sci. 25(6), 300–302 (2000)
Wittenbrink, C.M., Pang, A.T., Lodha, S.K.: Glyphs for Visualizing Uncertainty in Vector Fields. Proceedings of IEEE Transactions on Visualization and Computer Graphics 2(3), 266–279 (1996)
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Pintilie, G.D., Tuekam, B., Hogue, C.W.V. (2005). Generation of Glyphs for Conveying Complex Information, with Application to Protein Representations. In: Butz, A., Fisher, B., Krüger, A., Olivier, P. (eds) Smart Graphics. SG 2005. Lecture Notes in Computer Science, vol 3638. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11536482_8
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DOI: https://doi.org/10.1007/11536482_8
Publisher Name: Springer, Berlin, Heidelberg
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