Automated tracking and modeling of microtubule dynamics

M. Saban 1, A. Altinok 2, A. Peck 3, C. Kenney 1, S. Feinstein 3, L. Wilson 3, K. Rose 1, B. S. Manjunath 1
Center for Bio-image Informatics
1 Dept. of Electrical and Computer Engineering,
2 Dept. of Computer Science,
3 Dept. of Molecular, Cellular and Developmental Biology
University of California Santa Barbara, Santa Barbara, CA 93106
website: http://www.bioimage.ucsb.edu

Abstract

The method of microtubule tracking and dynamics analysis, presented here, improves upon the current means of manual and automated quantification of microtubule behavior. Key contributions are increasing accuracy and data volume, eliminating user bias and providing advanced analysis tools for the discovery of temporal patterns in cellular processes. By tracking the entire length of each resolvable microtubule, as opposed to only the tip, it is possible to boost dynamics studies with positional information that is virtually impossible to collect manually. We demonstrate the method on the analysis of a microtubule dataset, which was manually tracked and analyzed in the study of ╬▓III-tubulin isoform. Our results show that automated recognition of temporal patterns in cellular processes offers a highly promising potential.
[PDF] [BibTex]
Motaz El-Saban, Alphan Altinok, Austin Peck, Charles Kenney, Stuart Feinstein, Leslie Wilson, Kenneth Rose and B.S Manjunath,
IEEE International Symposium on Biomedical Imaging (ISBI), Crystal City, CA, Apr. 2006.
Node ID: 434 , DB ID: 237 , VRLID: 152 , Lab: VRL , Target: Proceedings