Modeling Approaches to Renal Systems Biology
A current goal in renal physiology is to understand the mechanisms involved in the function and regulation of each segment of the nephron at a cellular and molecular level. This dissertation describes three studies, presented in chapters 2 – 4, which pertain to various aspects of the systems biology of the kidney. A well-studied water channel in the renal collecting duct is aquaporin-2 (AQP2). AQP2 is regulated in part via vasopressin-mediated changes in protein half-life that are in turn dependent on AQP2 ubiquitination. The E3 ligase that marks AQP2 for ubiquitination and thus degradation is unknown. In chapter 2 I bioinformatically identify all E3 ligase genes coded by the human genome. I also developed a methodology built around Bayes' theorem that integrates information from multiple large-scale proteomic and transcriptomic datasets to rank order all 377 E3 ligases with respect to their probability of interaction with AQP2. In chapter 3, I describe a Java-based program called curated database Basic Local Alignment Search Tool (cdbBLAST), which uses the NCBI BLAST kernel to search for specific amino acid sequences corresponding to proteins in the database. cdbBLAST reports information on the matched protein and identifies proteins in the database that have similar sequences. Database searching based on protein sequence removes ambiguities arising from the standard search method based on official gene symbols, and allows the user efficient identification of related proteins that may fulfill the same functional roles. In the third study, I developed a model to simulate the stochastic nature of transcription using the transcript half-life and rate of transcription as input parameters. I describe the model in chapter 4 and show that the results fit a negative binomial distribution. I describe how we obtained the best fit parameters for that distribution as well as an estimate of the dropout percentage for our model output.
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