Stochastic models for cell motion and taxis
dc.contributor.author | Oster, George F. | en_US |
dc.contributor.author | Ionides, Edward L. | en_US |
dc.contributor.author | Rivkah Isseroff, R. | en_US |
dc.contributor.author | Fang, Kathy S. | en_US |
dc.date.accessioned | 2006-09-11T18:24:49Z | |
dc.date.available | 2006-09-11T18:24:49Z | |
dc.date.issued | 2004-01 | en_US |
dc.identifier.citation | Ionides, Edward L.; Fang, Kathy S.; Rivkah Isseroff, R.; Oster, George F.; (2004). "Stochastic models for cell motion and taxis." Journal of Mathematical Biology 48(1): 23-37. <http://hdl.handle.net/2027.42/46949> | en_US |
dc.identifier.issn | 0303-6812 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/46949 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=14685770&dopt=citation | en_US |
dc.description.abstract | Certain biological experiments investigating cell motion result in time lapse video microscopy data which may be modeled using stochastic differential equations. These models suggest statistics for quantifying experimental results and testing relevant hypotheses, and carry implications for the qualitative behavior of cells and for underlying biophysical mechanisms. Directional cell motion in response to a stimulus, termed taxis, has previously been modeled at a phenomenological level using the Keller-Segel diffusion equation. The Keller-Segel model cannot distinguish certain modes of taxis, and this motivates the introduction of a richer class of models which is nevertheless still amenable to statistical analysis. A state space model formulation is used to link models proposed for cell velocity to observed data. Sequential Monte Carlo methods enable parameter estimation via maximum likelihood for a range of applicable models. One particular experimental situation, involving the effect of an electric field on cell behavior, is considered in detail. In this case, an Ornstein- Uhlenbeck model for cell velocity is found to compare favorably with a nonlinear diffusion model. | en_US |
dc.format.extent | 197048 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Springer-Verlag; Springer-Verlag Berlin Heidelberg | en_US |
dc.subject.other | Cell Migration | en_US |
dc.subject.other | Galvanotaxis | en_US |
dc.subject.other | Stochastic Model | en_US |
dc.subject.other | Chemotaxis | en_US |
dc.subject.other | Mathematics | en_US |
dc.subject.other | Nonlinear Diffusion | en_US |
dc.title | Stochastic models for cell motion and taxis | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Natural Resources and Environment | en_US |
dc.subject.hlbsecondlevel | Molecular, Cellular and Developmental Biology | en_US |
dc.subject.hlbsecondlevel | Ecology and Evolutionary Biology | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Statistics, University of Michigan, Ann Arbor, MI, 48109, USA, | en_US |
dc.contributor.affiliationother | Department of Dermatology, University of California, Davis, CA, 95616, USA, | en_US |
dc.contributor.affiliationother | Department of Dermatology, University of California, Davis, CA, 95616, USA, | en_US |
dc.contributor.affiliationother | Department of Molecular and Cellular Biology, University of California, Berkeley, CA, 94720, USA, | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.identifier.pmid | 14685770 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/46949/1/285_2003_Article_220.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1007/s00285-003-0220-z | en_US |
dc.identifier.source | Journal of Mathematical Biology | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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