Literature DB >> 19877948

Quantification and regulation of cell migration.

K Zygourakis1.   

Abstract

Cell migration is essential for many physiological and pathological processes that include embryonic development, the immune response, wound healing, angiogenesis, and cancer metastasis. It is also important for emerging tissue engineering applications such as tissue reconstitution and the colonization of biomedical implants. By summarizing results from recent experimental and theoretical studies, this review outlines the role played by growth factors or substrate-adhesion molecules in modulating cell motility and shows that cell motility can be an important factor in determining the rates of tissue formation. The application of cell motility assays and the use of theoretical models for analyzing cell migration and proliferation are also discussed.

Entities:  

Year:  1996        PMID: 19877948     DOI: 10.1089/ten.1996.2.1

Source DB:  PubMed          Journal:  Tissue Eng        ISSN: 1076-3279


  5 in total

1.  Migration of isogenic cell lines quantified by dynamic multivariate analysis of single-cell motility.

Authors:  Mark P Harris; Eric Kim; Brandy Weidow; John P Wikswo; Vito Quaranta
Journal:  Cell Adh Migr       Date:  2008 Apr-May       Impact factor: 3.405

2.  Development and migration of plasma cells in the mouse lymph node.

Authors:  David R Fooksman; Tanja A Schwickert; Gabriel D Victora; Michael L Dustin; Michel C Nussenzweig; Dimitris Skokos
Journal:  Immunity       Date:  2010-07-08       Impact factor: 31.745

3.  Correlation of cell membrane dynamics and cell motility.

Authors:  Merlin Veronika; Roy Welsch; Alvin Ng; Paul Matsudaira; Jagath C Rajapakse
Journal:  BMC Bioinformatics       Date:  2011-11-30       Impact factor: 3.169

4.  Computational analysis of mRNA expression profiles identifies the ITG family and PIK3R3 as crucial genes for regulating triple negative breast cancer cell migration.

Authors:  Sukhontip Klahan; Mei-Shin Wu; Edward Hsi; Chi-Cheng Huang; Ming-Feng Hou; Wei-Chiao Chang
Journal:  Biomed Res Int       Date:  2014-05-06       Impact factor: 3.411

5.  Sub-population analysis based on temporal features of high content images.

Authors:  Merlin Veronika; James Evans; Paul Matsudaira; Roy Welsch; Jagath Rajapakse
Journal:  BMC Bioinformatics       Date:  2009-12-03       Impact factor: 3.169

  5 in total

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