Chemometric Strategies for the Analysis of Multivariate Chemical and Biological Measurements

Developments in analytical measurement science have led to unprecedented advances in our understanding of biological systems and medicine. The ability to measure increasing numbers of biological molecules at decreasing concentration levels in complex systems provides new insights into the function of biological organisms, and these capabilities will continue to expand. However, the collection and interpretation of relevant data in the so-called "omics" sciences remains a challenge for high-throughput biological methods. This research addresses those challenges through the development of novel approaches to visualize and interpret the massive amounts of data, transforming measurements into information. Additionally, new strategies are proposed to increase the throughput and utility of methods employed in proteomics. The core of this work draws on the applicant's expertise in the fields of chemometrics and bioinformatics, which relate to the application of statistical, mathematical and computer-based methods for the extraction of information from chemical and biological measurements, respectively. Modern analytical systems typically provide measurements on thousands of chemical entities (genetic material, proteins, metabolites, etc.) in a single biological sample, referred to as multivariate or high-dimensional data. Even so, the critical information sought (e.g. identification of a disease biomarker) may not be obtained for several reasons that include: (1) the absence of the critical molecule(s) in the data, (2) the inability to distinguish the important signal(s) from the meaningless ones, and (3) a statistically insufficient number of samples due to long analysis times. This research will address these issues by enhancement of the measurement and data analysis methods used omics research, leading to the extraction of more reliable information. Ultimately, this is expected to have important implications for the study of biology and medicine.