Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Analytical Chemistry (1)
- Analytical, Diagnostic and Therapeutic Techniques and Equipment (1)
- Applied Statistics (1)
- Biochemical Phenomena, Metabolism, and Nutrition (1)
- Biochemistry (1)
-
- Biochemistry, Biophysics, and Structural Biology (1)
- Cardiology (1)
- Cardiovascular Diseases (1)
- Chemistry (1)
- Computational Biology (1)
- Computer Sciences (1)
- Diagnosis (1)
- Diseases (1)
- Genetics and Genomics (1)
- Medical Biomathematics and Biometrics (1)
- Medical Molecular Biology (1)
- Medical Sciences (1)
- Medical Specialties (1)
- Medicine and Health Sciences (1)
- Molecular Biology (1)
- Programming Languages and Compilers (1)
- Statistical Methodology (1)
- Systems Biology (1)
- Theory and Algorithms (1)
Articles 1 - 2 of 2
Full-Text Articles in Biostatistics
Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor
Electronic Theses and Dissertations
Metabolomics, the study of small molecules in biological systems, has enjoyed great success in enabling researchers to examine disease-associated metabolic dysregulation and has been utilized for the discovery biomarkers of disease and phenotypic states. In spite of recent technological advances in the analytical platforms utilized in metabolomics and the proliferation of tools for the analysis of metabolomics data, significant challenges in metabolomics data analyses remain. In this dissertation, we present three of these challenges and Bayesian methodological solutions for each. In the first part we develop a new methodology to serve a basis for making higher order inferences in metabolomics, …
Compound Identification Using Penalized Linear Regression., Ruiqi Liu
Compound Identification Using Penalized Linear Regression., Ruiqi Liu
Electronic Theses and Dissertations
In this study, we propose a new method for compound identification using penalized linear regression. Compound identification is often achieved by matching the experimental mass spectra to the mass spectra stored in a reference library based on mass spectral similarity. In the context of the linear regression, the response variable is an experimental mass spectrum (i.e., query) and all the compounds in the reference library are the independent variables. However, the number of compounds in the reference library is much larger than the range of m/z values so that the data become high dimensional data with suffering from singularity. For …