Abstract
The MET protein controls growth, invasion, and metastasis in cancer cells and is thereby of interest to study, for example from a structural point of view. For individual particle imaging by Cryo-Electron Tomography of the MET protein, or other proteins, dedicated image analysis methods are required to extract information in a robust way as the images have low contrast and resolution (with respect to the size of the imaged structure). We present a method to identify the two parts of the MET protein, β-propeller and stalk, using a fuzzy framework. Furthermore, we describe how a representation of the MET stalk, denoted stalk curve, can be identified based on the use of non-uniform B-splines. The stalk curve is used to extract relevant geometrical information about the stalk, e.g., to facilitate curvature and length measurements.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Birchmeier, C., Birchmeier, W., Gherardi, E., Vande Woude, G.F.: Met, metastasis, motility and more. Nature Reviews Molecular Cell Biology 4, 915–925 (2003)
Gherardi, E., Sandin, S., Petoukhov, M.V., Finch, J., Youles, M.E., Öfverstedt, L.G., Miguel, R.N., Blundell, T.L., Vande Woude, G.F., Skoglund, U., Svergun, D.I.: Structural basis of hepatocyte growth factor/scatter factor and MET signalling. Proc. National Academy of Sciences (PNAS) 103(11), 4046–4051 (2006)
Skoglund, U., Öfverstedt, L.G., Burnett, R.M., Bricogne, G.: Maximum-entropy three-dimensional reconstruction with deconvolution of the contrast transfer function: A test application with adenovirus. J. Structural Biology 117, 173–188 (1996)
Laing, M.: An introduction to the scope, potential and applications of X-ray analysis. International Union of Crystallographers Teaching Pamphlets (1981)
Atta-ur Rahman, H.E.J.: Nuclear Magnetic Resonance: Basic Principles. Springer, New York (1986)
Yu, Z., Bajaj, C.: Automatic ultrastructure segmentation of reconstructed cryoem maps of icosahedral viruses. IEEE Trans. Image Processing 14(9), 1324–1337 (2005)
Volkmann, N.: A novel three-dimensional variant of the watershed transform for segmentation of electron density maps. J. of Structural Biology 138, 123–129 (2002)
Svensson, S., Gedda, M., Fanelli, D., Skoglund, U., Öfverstedt, L.G., Sandin, S.: Using a fuzzy framework for delineation and decomposition of immunoglobulin G in cryo electron tomographic images. In: Tang, Y.Y., Wang, S.P., Lorette, G., Yeung, D.S., Yan, H. (eds.) ICPR 2006. Proc. The 18th International Conference on Pattern Recognition, vol. 4, pp. 687–690. IEEE Computer Society Press, Los Alamitos (2006)
Bongini, L., Fanelli, D., Svensson, S., Gedda, M., Piazza, F., Skoglund, U.: Resolving the geometry of biomolecules as seen by cryo electron tomography. Journal of Microscopy (accepted for publication, 2007)
Watt, A.: 3D Computer Graphics, 3rd edn. Addison-Wesley, London, UK (2000)
Coeurjolly, D., Svensson, S.: Estimation of curvature along curves with application to fibres in 3D images of paper. In: Bigun, J., Gustavsson, T. (eds.) SCIA 2003. LNCS, vol. 2749, pp. 247–254. Springer, Heidelberg (2003)
Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)
Vincent, L., Soille, P.: Watersheds in digital spaces: An efficient algorithm based on immersion simulations. IEEE Trans. on Pattern Analysis and Machine Intelligence 13(6), 583–597 (1991)
Saha, P.K., Wehrli, F.W., Gomberg, B.R.: Fuzzy distance transform: theory, algorithms, and applications. Comput. Vis. Image Underst. 86(3), 171–190 (2002)
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. John Wiley & Sons, New York, USA (2001)
Levi, G., Montanari, U.: A grey-weighted skeleton. Information and Control 17, 62–91 (1970)
Fouard, C., Gedda, M.: An objective comparison between gray weighted distance transforms and weighted distance transforms on curved spaces. In: Kuba, A., Nyúl, L.G., Palágyi, K. (eds.) DGCI 2006. LNCS, vol. 4245, pp. 259–270. Springer, Heidelberg (2006)
Wall, K., Danielsson, P.E.: A fast sequential method for polygonial approximation of digitized curves. Computer Vision, Graphics, and Image Processing 28, 220–227 (1984)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gedda, M., Svensson, S. (2007). Flexibility Description of the MET Protein Stalk Based on the Use of Non-uniform B-Splines. In: Kropatsch, W.G., Kampel, M., Hanbury, A. (eds) Computer Analysis of Images and Patterns. CAIP 2007. Lecture Notes in Computer Science, vol 4673. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74272-2_22
Download citation
DOI: https://doi.org/10.1007/978-3-540-74272-2_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74271-5
Online ISBN: 978-3-540-74272-2
eBook Packages: Computer ScienceComputer Science (R0)