MicroRNAs (miRNAs) may serve as diagnostic and predictive biomarkers for cancer. The aim of this study was to identify novel cancer biomarkers from miRNA datasets, in addition to those already known. Three published miRNA cancer datasets (liver, breast, and brain) were evaluated, and the performance of the entire feature set was compared to the performance of individual feature filters, an ensemble of those filters, and a support vector machine (SVM) wrapper. In addition to confirming many known biomarkers, the main contribution of this study is that seven miRNAs have been newly identified by our ensemble methodology as possible important biomarkers for hepatocellular carcinoma or breast cancer, pending wet lab confirmation. These biomarkers were identified from miRNA expression datasets by combining multiple feature selection techniques (i.e., creating an ensemble) or by the SVM-wrapper, and then classified by different learners. Generally speaking, creating a subset of features by selecting only the highest ranking features (miRNAs) improved upon results generated when using all the miRNAs, and the ensemble and SVM-wrapper approaches outperformed individual feature selection methods. Finally, an algorithm to determine the number of top-ranked features to include in the creation of feature subsets was developed. This algorithm takes into account the performance improvement gained by adding additional features compared to the cost of adding those features. / by Alex Kotlarchyk. / Thesis (Ph.D.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.

Indiana University-Purdue University Indianapolis (IUPUI) / Cancer is still among those diseases that prominently contribute to the numerous deaths that are caused each year. But as technology and research is reaching new zeniths in the present times, cure or early detection of cancer is possible. The detection of rare cells can help understand the origin of many diseases. The current study deals with one such technology that is used for the capture or effective separation of these rare cells called Lab-on-a-chip microchip technology. The isolation and capture of rare cells is a problem uniquely suited to microfluidic devices, in which geometries on the cellular length scale can be engineered and a wide range of chemical functionalizations can be implemented. The performance of such devices is primarily affected by the chemical interaction between the cell and the capture surface and the mechanics of cell-surface collision and adhesion. This study focuses on the fundamental adhesion and transport mechanisms in rare cell-capture microdevices, and explores modern device design strategies in a transport context. The biorheology and engineering parameters of cell adhesion are defined; chip geometries are reviewed. Transport at the microscale, cell-wall interactions that result in cell motion across streamlines, is discussed. We have concentrated majorly on the fluid dynamics design of the chip. A simplified description of the device would be to say that the chip is at micro scale. There are posts arranged on the chip such that the arrangement will lead to a higher capture of rare cells. Blood consisting of rare cells will be passed through the chip and the posts will pose as an obstruction so that the interception and capture efficiency of the rare cells increases. The captured cells can be observed by fluorescence microscopy. As compared to previous studies of using solid microposts, we will be incorporating a new concept of cylindrical shell micropost. This type of micropost consists of a solid inner core and the annulus area is covered with a forest of silicon nanopillars. Utilization of such a design helps in increasing the interception and capture efficiency and reducing the hydrodynamic resistance between the cells and the posts. Computational analysis is done for different designs of the posts. Drag on the microposts due to fluid flow has a great significance on the capture efficiency of the chip. Also, the arrangement of the posts is important to contributing to the increase in the interception efficiency. The effects of these parameters on the efficiency in junction with other factors have been studied and quantified. The study is concluded by discussing design strategies with a focus on leveraging the underlying transport phenomena to maximize device performance.