Browsing by Subject "SVD"
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Item Glycomics : integration of lectin and gene expression microarray data(2011-08) Pilobello, Kanoelani Takaishi; Mahal, Lara K.; Anslyn, Eric V., 1960-Glycomics is the systematic study of glycosylation in the context of a whole cell or organism. Glycosylated proteins are estimated to make up 50% of all proteins and cover the outside of the cell. Functional roles in glycosylation have been noted in pathogenesis, metastasis, and embryogenesis. However, the structure of these carbohydrates has been difficult to study due to the chemical nature of carbohydrates. Lectins, carbohydrate binding proteins excluding antibodies and enzymes, can be utilized to study glycosylation in a high throughput manner using a microarray format. Glycans, the carbohydrates attached to a protein or lipid, are not synthesized from a template. They are added co- or post-translationally by a concerted set of enzymes in the secretory pathway. In addition, the glycan structures may be altered by metabolism or trafficking. Cell type specific glycosylation has long been hypothesized due to observations of bacteria homing to tissues. We use lectin microarray technology to define the glycosylation in a subset of the NCI-60, a set of cell lines from different tissues. Using a customized gene expression microarray, we identify cell type dependent glycosylation genes and observe evidence of cell type dependent spliceforms for an O-glycosylated mucin. Data from the lectin microarray and a published gene expression data set were integrated using Generalized Singular Value Decomposition (GSVD), a linear matrix decomposition method. We have successfully decomposed the data into 3 cell type dependent meta patterns that segregate by glycosylation family. Correlation projection of the genes and subsequent gene ontology enrichment suggests that genes in different pathways covary with the types of glycosylation. An inverse relationship was revealed for the N- glycosylation pattern between the SVD of the lectins and the GSVD of the genes and lectins together. Whereas, the relationship was correlative for O-glycosylation, which was clearly illustrated in biplots. This work argues that types of glycosylation are regulated by different mechanisms in different cell types.Item A thermodynamic definition of protein folds(2008-05-01) Jason Vertrees; Robert Fox; Wlodek Bujalowski; Vincent Hilser; Montgomery Pettitt; Henry EpsteinModern techniques in structural biology, like homology modeling, protein threading, protein fold classification, and homology detection have proven extremely useful. For example, they have provided us with evolutionary information about protein homology which has in some many cases lead directly to therapeutics. Due to the importance of these methods, augmenting or improving them may lead to significant advances in understanding proteins. These methods treat the high-resolution structure as a static entity upon which they operate, however we know that proteins are not static entities---they are polymers that exist in an enormous array of conformational states. Therefore, we propose to model the proteins from a statistical thermodynamic viewpoint based upon their average energetic properties. We show that this model can be used to (1) better characterize the partial unfolding process of proteins, and (2) reclassify the protein fold space from a new perspective.Item Understanding Spatio-Temporal Variability and Associated Physical Controls of Near-Surface Soil Moisture in Different Hydro-Climates(2013-05-06) Joshi, ChampaNear-surface soil moisture is a key state variable of the hydrologic cycle and plays a significant role in the global water and energy balance by affecting several hydrological, ecological, meteorological, geomorphologic, and other natural processes in the land-atmosphere continuum. Presence of soil moisture in the root zone is vital for the crop and plant life cycle. Soil moisture distribution is highly non-linear across time and space. Various geophysical factors (e.g., soil properties, topography, vegetation, and weather/climate) and their interactions control the spatio-temporal evolution of soil moisture at various scales. Understanding these interactions is crucial for the characterization of soil moisture dynamics occurring in the vadose zone. This dissertation focuses on understanding the spatio-temporal variability of near-surface soil moisture and the associated physical control(s) across varying measurement support (point-scale and passive microwave airborne/satellite remote sensing footprint-scale), spatial extents (field-, watershed-, and regional-scale), and changing hydro-climates. Various analysis techniques (e.g., time stability, geostatistics, Empirical Orthogonal Function, and Singular Value Decomposition) have been employed to characterize near-surface soil moisture variability and the role of contributing physical control(s) across space and time. Findings of this study can be helpful in several hydrological research/applications, such as, validation/calibration and downscaling of remote sensing data products, planning and designing effective soil moisture monitoring networks and field campaigns, improving performance of soil moisture retrieval algorithm, flood/drought prediction, climate forecast modeling, and agricultural management practices.