Modeling a Cellular Response to a Gradient Mathematics and Molecular Biology Inform a Mechanistic Understanding
| dc.contributor.author | Ge, Xuan | |
| dc.contributor.author | Stonko, David | |
| dc.date.accessioned | 2025-12-15T14:58:54Z | |
| dc.date.issued | 2012 | |
| dc.description.abstract | Cell migration is prevalent in normal development of all animals, and pathological conditions like birth defects or metastatic cancers can arise when this process goes awry. Understanding the phenomenon of cells undergoing the transition from a stationary state to a migratory stage is of broad interest. Such a complex problem can be more easily studied in a simple organism, such as the fruit fly Drosophila melanogaster (Naora and Montell, 2005). Drosophila is one of the most studied organisms in biological research. Its short generation time, high fecundity, visible congenital markers, and well-characterizedgenome are just a few of the many traits that make it an ideal organismfor genetic studies. In addition, about eighty percent of disease genes in humans encode proteins that are conserved in flies (Reiter et al., 2001). Thus, because the underlying molecular signaling mechanisms are well conserved, insight into cell migration gleaned from Drosophila will likely be broadly applicable. | |
| dc.description.sponsorship | The authors thank the members of the Starz-Gaiano laboratory for experimental assistance and members of the Undergraduate Biology/Mathematics program (UBM@UMBC) for helpful discussions and support. We used the following databases in our work: http:// www.microrna.org/micror na/home.do and http://flybase.org/. We also acknowledge the following funding sources: NSF-UBM to DS, SG, BEP, XG (PIs Dr. Leips and Dr. N. Neerchal); NSF-Career to MSG; UMBC Start-Up funding to BEP and MSG. | |
| dc.description.uri | https://ur.umbc.edu/wp-content/uploads/sites/354/2020/04/umbcReview2012.pdf#page=90 | |
| dc.format.extent | 24 pages | |
| dc.genre | journal articles | |
| dc.identifier | doi:10.13016/m23vno-hbff | |
| dc.identifier.citation | Ge, Xuan, and David Stonko. “Modeling a Cellular Response to a Gradient Mathematics and Molecular Biology Inform a Mechanistic Understanding.” UMBC Review: Journal of Undergraduate Research 13 (2012): 90-113. https://ur.umbc.edu/wp-content/uploads/sites/354/2020/04/umbcReview2012.pdf#page=90. | |
| dc.identifier.uri | http://hdl.handle.net/11603/41282 | |
| dc.language.iso | en | |
| dc.publisher | University of Maryland, Baltimore County | |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Biological Sciences Department | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.relation.ispartof | UMBC Review | |
| dc.relation.ispartof | UMBC Mathematics and Statistics Department | |
| dc.relation.ispartof | UMBC Honors College | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.title | Modeling a Cellular Response to a Gradient Mathematics and Molecular Biology Inform a Mechanistic Understanding | |
| dc.type | Text | |
| dcterms.creator | https://orcid.org/0000-0002-2804-2857 |
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