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A model for glioma growth This paper was submitted as an invited paper resulting from “Understanding Complex Systems” conference held at University of Illinois-Urbana Champaign, May 2005

dc.contributor.authorKhain, Evgeniyen_US
dc.contributor.authorSander, Leonard M.en_US
dc.contributor.authorStein, Andrew M.en_US
dc.date.accessioned2006-12-07T16:52:50Z
dc.date.available2006-12-07T16:52:50Z
dc.date.issued2005-11en_US
dc.identifier.citationKhain, Evgeniy; Sander, Leonard M.; Stein, Andrew M. (2005)."A model for glioma growth This paper was submitted as an invited paper resulting from “Understanding Complex Systems” conference held at University of Illinois-Urbana Champaign, May 2005 ." Complexity 11(2): 53-57. <http://hdl.handle.net/2027.42/48771>en_US
dc.identifier.issn1076-2787en_US
dc.identifier.issn1099-0526en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/48771
dc.description.abstractGlioblastoma Multiforme (GBM) is the most invasive form of primary brain tumor. We propose a mathematical model that describes such tumor growth and allows us to describe two different mechanisms of cell invasion: diffusion (random motion) and chemotaxis (directed motion along the gradient of the chemoattractant concentration). The results are in a quantitative agreement with recent in vitro experiments. It was observed in experiments that the outer invasive zone grows faster than the inner proliferative region. We argue that this feature indicates transient behavior, and that the growth velocities tend to the same constant value for larger times. A longer-time experiment is needed to verify this hypothesis and to choose between the two basic mechanisms for tumor growth. © 2005 Wiley Periodicals, Inc. Complexity 11: 53–57, 2005en_US
dc.format.extent161948 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherWiley Subscription Services, Inc., A Wiley Companyen_US
dc.subject.otherMathematics and Statisticsen_US
dc.titleA model for glioma growth This paper was submitted as an invited paper resulting from “Understanding Complex Systems” conference held at University of Illinois-Urbana Champaign, May 2005en_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelScience (General)en_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Physics and Michigan Center for Theoretical Physics, The University of Michigan, Ann Arbor, Michigan 48109en_US
dc.contributor.affiliationumDepartment of Physics and Michigan Center for Theoretical Physics, The University of Michigan, Ann Arbor, Michigan 48109 ; Randall Laboratory of Physics, University of Michigan, Ann Arbor, MI 48109-1120en_US
dc.contributor.affiliationumDepartment of Mathematics, The University of Michigan, Ann Arbor, Michigan 48109en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/48771/1/20108_ftp.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1002/cplx.20108en_US
dc.identifier.sourceComplexityen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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