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• W2254564188 abstract "The goal of my thesis was to discover novel peptide hormones (PH) in the human genome. Peptide hormones (PH) are an important class of molecules that are involved in a broad range of normal and pathological physiological processes. PH are small secreted proteins that are processed from larger proteins, called precursors. In the first part of the thesis I introduce hidden Markov models (HMM)-based algorithms that allow for the modelling of those PH precursor sequences. This leads me to derive models of some of their well-known characteristic features, including signal peptides and prohormone convertase cleavage sites. Next, I make use of orthology information and modify the HMM algorithms so that the HMM can incorporate a conservation score that is calculated along protein sequence alignments. I show that this idea brings significant improvements in the quality of predictions and I conclude the chapter by drawing a list of potential candidate peptide hormones that was obtained by running the HMM algorithms on genome-wide protein sequence data. In the second and third part of the thesis I present data on the most interesting candidates that we named spexin and augurin. I show in vitro subcellular localization, secretion and processing of those proteins after transfection of their coding DNA into endocrine cells. I then show mRNA and protein in vivo expression data in the mouse for those two proteins, and present functional data on spexin. I conclude both chapters by making some speculations on the functional significance of those two proteins. In the fourth part of the thesis I present data on the expression, secretion and processing of four extra candidate peptide hormones." @default.
• W2254564188 created "2016-06-24" @default.
• W2254564188 creator A5029137625 @default.
• W2254564188 date "2008-01-30" @default.
• W2254564188 modified "2023-09-23" @default.
• W2254564188 title "Searching for novel peptide hormones in the human genome" @default.
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