Glycans and their conjugates form the largest and most diverse class of biological molecules found within nature. These glycosides are vital for numerous cellular functions including recognition events, protein stabilisation and energy storage, to name a few. Additionally, abnormalities within these structures are associated with a wide range of disease states. As a result, robust analytical techniques capable of in depth characterisation of carbohydrates and their binding partners are required. Currently, liquid chromatography coupled with tandem mass spectrometry (MS2) is the 'gold standard' for characterising these species. However there are inherent challenges for 'sequencing' carbohydrates given that most structures are diastereomeric. As a result MS alone is insufficient to fully elucidate all stereochemical and often regiochemical information and alternative analytical techniques have inherent issues meaning that they are not suitable for medium/high throughput analysis. To facilitate elucidation of these structures, ion mobility spectrometry (IMS) has been used in-line with MS2. IMS of mono- and di-saccharide product ions generate by collision-induced dissociation (CID) of various glycans and their conjugates enables unambiguous identification of the monomer and the regio-/stereo-chemistry of the glycosidic bond, independent of the precursor structure. Also, given the prominence of glycans in biological recognition events, high-throughput techniques capable of elucidating and characterising carbohydrate to glycan-binding protein (GBP) interactions are highly sought after. Historically, (micro)array strategies are employed to screen large numbers of biological interactions, with detection conventionally achieved with fluorescent tagging. The major disadvantage of this approach is the requirement of a labelling step to facilitate detection of glycan-GBP binding. MS offers the ability to unambiguously identify GBPs when combined with routine bottom-up proteomics strategies, namely on-chip proteolysis followed by mass fingerprinting and MS2 analysis and subsequent comparison to protein databases. It is anticipated that these methodologies developed throughout these studies, both for carbohydrate sequencing and the characterisation of glycan-binding proteins, will greatly add to the Glycomics toolbox.

The characterization of biomolecules and biomolecular complexes represents an area of significant research activity because of the link between structure and function. Drug development relies on structural information in order to target certain domains. Many traditional biochemical techniques, however, are limited by their ability to characterize only certain stable forms of a molecule. As a result, multidimensional approaches, such as ion mobility mass spectrometry coupled to mass spectrometry (IMS-MS), are becoming very attractive tools as they provide fast separation, detection and identification of molecules, in addition to providing three-dimensional shape for structural elucidation. The present work expands the use and application of trapped ion mobility spectrometry-coupled to mass spectrometry (TIMS-MS) by analyzing a range of biomolecules (including proteoforms, intrinsically disordered peptides, DNA and molecular complexes). The aim is to i) evaluate the TIMS platform measuring sensitivity, selectivity, and separation of targeted compounds, ii) pioneer new applications of TIMS for a more efficient and higher throughput methodologies for identification and characterization of biomolecular ions, and iii) characterize the dynamics of selected biomolecules for insight into the folding pathways and the intra-or intermolecular interactions that define their conformational space.

After a Radiological Dispersal Device (RDD) event, there will not be time to transport people to a whole-body-counter (WBC), since it is a specialized instrument. This work will assess the feasibility of using handheld spectrometers for measuring the radioactivity that may have been inhaled by a victim as a consequence of an RDD event. Measurements were made with a handheld isotope identifier using a slab phantom and several radioactive point sources. A Lawrence Livermore National Laboratory (LLNL) Realistic Torso Phantom and a set of phantoms based on Medical Internal Radiation Dose (MIRD) reports were also used in this work. These phantoms include the human skeleton and have tissue-equivalent organs. Computational models were developed of all of the phantoms using the Monte Carlo Transport code MCNP. After validation of the computer model, MCNP runs were conducted using other sources that are likely to be used in a RDD. Calculations were then done to find the Minimum Detectable Activity (MDA) of all sources used. The Minimum Detectable Dose (MDD) was then calculated for the MIRD phantoms at various times after inhalation.

High-throughput techniques are currently some of the most promising methods to study molecular biology, with the potential to improve medicine and enable new biological applications. In proteomics, the large scale study of proteins, the leading method is mass spectrometry. At present researchers can routinely identify and quantify thousands of proteins in a single experiment with the technique called shotgun proteomics. A challenge of these experiments is the computational analysis and the interpretation of the mass spectra. A shotgun proteomics experiment easily generates tens of thousands of spectra, each thought to represent a peptide from a protein. Due to the immense biological and technical complexity, however, our computational tools often misinterpret these spectra and derive incorrect peptides. As a consequence, the biological interpretation of the experiment relies heavily on the statistical confidence that we estimate for the identifications. In this thesis, I have included four articles from my research on the accuracy of the statistical confidence estimates in shotgun proteomics, how to accomplish and evaluate it. In the first two papers a new method to use pre-characterized protein samples to evaluate this accuracy is presented. The third paper deals with how to avoid statistical inaccuracies when using machine learning techniques to analyze the data. In the fourth paper, we present a new tool for analyzing shotgun proteomics results, and evaluate the accuracy of  its statistical estimates using the method from the first papers. The work I have included here can facilitate the development of new and accurate computational tools in mass spectrometry-based proteomics. Such tools will help making the interpretation of the spectra and the downstream biological conclusions more reliable.

The level structures of ('94)Ru, ('90)Mo, ('88)Zr, ('89)Mo and ('89)Nb have been studied via the decay of two isomers of ('94)Rh, two of ('90)Tc, two of ('88)Nb, one of ('89)Tc and one of ('89)Mo, respectively. These nuclides were produced via the proton bombardment of isotopically-enriched ('96)Ru and ('92)Mo as well as naturally-occurring Zr. Using gamma and beta spectroscopy techniques, detailed level schemes have been produced. / High-spin states in ('89)Nb, ('88)Zr and ('88)Nb have been studied with in-beam gamma-ray spectroscopy techniques. These nuclides were produced with alpha particle-induced reactions on ('89)Y. A neutron-multiplicity experiment was used to identify the nucleus to which several gamma-rays belong. / The systematics of the N = 48 and 47 nuclei, along with theoretical descriptions based on the nuclear shell model, are discussed. Contributions to original knowledge are summarized in Chapter V.

Thesis (Ph.D.)--University of Wollongong, 2005. / Typescript. EMBARGOED-this thesis is subject to a six months embargo (07/09/06) and may only be viewed and copied with the permission of the author. For further information please Contact the Archivist. Includes bibliographical references: leaf 159-194.

Thesis (M.S.)--Montana State University--Bozeman, 2004. / Typescript. Chairperson, Graduate Committee: David Dickensheets. Includes bibliographical references (leaves 94-95).

Thesis (M.S.)--West Virginia University, 2005. / Title from document title page. Document formatted into pages; contains vii, 44 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 41-44).

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references. Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 1998. / Vita. Includes bibliographical references (leaf 171). Available also in a digital version from Dissertation Abstracts.