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Full-Text Articles in Engineering

Induction Of Differentiation Of Dental Pulp-Derived Mesenchymal Stem Cells (Dpsc), Aubrey Young Dec 2014

Induction Of Differentiation Of Dental Pulp-Derived Mesenchymal Stem Cells (Dpsc), Aubrey Young

UNLV Theses, Dissertations, Professional Papers, and Capstones

Mesenchymal stem cells are derived from a variety of human tissues and are being bioengineered and studied for possible uses in the advancement of medicine. Recent efforts are being focused on Dental Pulp Stem Cells (DPSC's) due to the accessibility of this tissue. Many factors influence DPSC quality and quantity, including the specific methods used to isolate, collect, concentrate, and store these isolates once they are removed. Ancillary factors, such as the choice of media, the selection of early versus late passage cells, and cryopreservation techniques may also influence the differentiation potential and proliferative capacity of DPSC isolates.

The objective …


An Algorithm For Identifying Novel Targets Of Transcription Factor Families: Application To Hypoxia-Inducible Factor 1 Targets, Yue Jiang, Bojan Cukic, Donald A. Adjeroh, Heath D. Skinner, Jie Lin, Qingxi J. Shen, Bing-Hua Jiang Jan 2009

An Algorithm For Identifying Novel Targets Of Transcription Factor Families: Application To Hypoxia-Inducible Factor 1 Targets, Yue Jiang, Bojan Cukic, Donald A. Adjeroh, Heath D. Skinner, Jie Lin, Qingxi J. Shen, Bing-Hua Jiang

Electrical & Computer Engineering Faculty Research

Efficient and effective analysis of the growing genomic databases requires the development of adequate computational tools. We introduce a fast method based on the suffix tree data structure for predicting novel targets of hypoxia-inducible factor 1 (HIF-1) from huge genome databases. The suffix tree data structure has two powerful applications here: one is to extract unknown patterns from multiple strings/sequences in linear time; the other is to search multiple strings/sequences using multiple patterns in linear time. Using 15 known HIF-1 target gene sequences as a training set, we extracted 105 common patterns that all occur in the 15 training genes …