<> "The repository administrator has not yet configured an RDF license."^^ . <> . . "Automated sample preparation for streamlined\r\nproteomic profiling of clinical specimens"^^ . "The genetic information of all life is encoded within DNA molecules that are translated into functional entities, so-called proteins. They are responsible for operating and controlling a vast array of molecular mechanisms in any biological system and ubiquitous in\r\n(patho)physiology as a result. Besides, proteins are the primary target of drugs and can\r\nhave a central role as biomarkers for diagnostic, prognostic, or predictive purposes. Here,\r\nmany regulatory mechanisms and spatiotemporal influences prevent an accurate\r\nprediction of a proteins’ abundance and its associated functionality based on the genome\r\ninformation alone. Nowadays, it has become possible to measure and quantify thousands\r\nof proteins simultaneously, however, involving comprehensive sample preparation\r\nprocedures. Currently, no universally standardized method enables a routine application of\r\nproteome profiling in a clinical environment.\r\nIn this thesis, an automated workflow for the efficient processing of the most common and\r\nquantity-limited specimens is described. In order to demonstrate the usefulness of the end-to-\r\nend pipeline, which was termed autoSP3, it was applied to the proteome profiling of\r\nhistologically defined and WHO recognized growth patterns of pulmonary adenocarcinoma\r\n(ADC) that currently have a limited clinical implication. Secondly, we investigated the\r\nproteome composition of a molecularly well-defined cohort of Ependymoma (EPN)\r\npediatric brain tumors. Despite the availability of substantial NGS data and their ability to\r\ndifferentiate nine distinct subgroups, the majority of tumors remained without a functional\r\ninsight. Here, the proteome profiling could provide a missing link and emphasize several\r\nsubgroup-specific protein targets.\r\nIn summary, this thesis describes the optimization of SP3 and its automation into a robust\r\nand cost-efficient pipeline for quantity-limited sample preparation and biological insight\r\ninto the proteome composition of ADC growth patterns and EPN tumor subgroups."^^ . "2020" . . . . . . "Torsten Michael"^^ . "Müller"^^ . "Torsten Michael Müller"^^ . . . . . . "Automated sample preparation for streamlined\r\nproteomic profiling of clinical specimens (PDF)"^^ . . . "Mueller_Torsten_Dissertation.pdf"^^ . . . "Automated sample preparation for streamlined\r\nproteomic profiling of clinical specimens (Other)"^^ . . . . . . "indexcodes.txt"^^ . . . "Automated sample preparation for streamlined\r\nproteomic profiling of clinical specimens (Other)"^^ . . . . . . "small.jpg"^^ . . . "Automated sample preparation for streamlined\r\nproteomic profiling of clinical specimens (Other)"^^ . . . . . . "medium.jpg"^^ . . . "Automated sample preparation for streamlined\r\nproteomic profiling of clinical specimens (Other)"^^ . . . . . . "preview.jpg"^^ . . . "Automated sample preparation for streamlined\r\nproteomic profiling of clinical specimens (Other)"^^ . . . . . . "lightbox.jpg"^^ . . "HTML Summary of #29046 \n\nAutomated sample preparation for streamlined \nproteomic profiling of clinical specimens\n\n" . "text/html" . . . "500 Naturwissenschaften und Mathematik"@de . "500 Natural sciences and mathematics"@en . . . "570 Biowissenschaften, Biologie"@de . "570 Life sciences"@en . . . "600 Technik, Medizin, angewandte Wissenschaften"@de . "600 Technology (Applied sciences)"@en . .