Spelling suggestions: "subject:"1genetic transcription -- 3research"" "subject:"1genetic transcription -- 1research""
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Heterologous expression and purification of cell function components -: an effort towards developing an antigen-capture ELISA diagnostics for metastatic cancersUnknown Date (has links)
Metastatic cancers are problematic because they spread throughout the body. A crucial step in cancer metastasis is the separation of the cancer cells from their surrounding normal cells. This occurs due to suppression or destruction of cell adhesion molecules such as E-cadherin, occludin, and various claudins. The Snail and Slug transcription factors play a direct role in suppressing these cell adhesion molecules through their SNAG repression domain. We explored the possibility of developing an ELISA diagnostics capable of detecting soluble E-cadherin, occludin, and claudin fragments in the serum of cancer patients. Using several bioinformatics tools, unique extracellular antigenic sequences were identified on claudins-1, 4, 16, occludin, and E-cadherin. These sequences were cloned as GST fusion proteins, expressed, and purified in large quantities to raise antibodies. In parallel, expression profiling of metastatic cancer cell lines was carried out to derive a correlation between Snail-Slug expression and suppression of cell adhesion molecules. / by Michael Irvine. / Thesis (M.S.)--Florida Atlantic University, 2009. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2009. Mode of access: World Wide Web.
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Stochastic modeling of eukaryotic transcription at the single nucleotide levelVashishtha, Saurabh January 2011 (has links)
DNA is the genetic material of a cell and is copied in the form of pre-mRNA through
transcription in eukaryotes. RNA polymerase II is responsible for the transcription of all
genes that express proteins. Transcription is a significant source of the stochasticity in
gene expression. In this thesis, I discuss the development of a biochemically detailed
model of eukaryotic transcription, which includes pre-initiation complex (PIC) assembly,
abortive initiation, promoter-proximal pausing and termination as the points that can be
slow steps for transcription. The stochastic properties of this model are studied in detail
by stochastic simulations with some preliminary mathematical analysis. The results of
this model suggest that PIC assembly can play the most significant role in affecting the
transcription dynamics. In addition, promoter-proximal pausing has been identified as a
potential noise regulatory step in eukaryotic transcription. These results show excellent
agreement with many experimental studies. / x, 107 leaves : ill. ; 29 cm
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