Improved Neuropeptide Identification Bioinformatics and Mass Spectrometry
نویسنده
چکیده
List of papers This thesis is based on the papers listed below, which are referred to in the text by Roman numerals I-V. Neuropeptidomics: MS applied to the discovery of novel peptides from the brain. An automated method for scanning LC-MS data sets for significant peptides and proteins, including quantitative profiling and interactive confirmation. Striatal proteomic analysis suggests that first L-dopa dose equates to chronic exposure. Abbreviations Į-MSH Į-melanocyte-stimulating hormone ACTH Adrenocorticotropin CAD Collision-activated dissociation CID Collision-induced dissociation ECD Electron capture dissociation ESI Electrospray ionization ETD Electron transfer dissociation FT-MS Fourier transform ion cyclotron HTML HyperText markup language LC Liquid chromatography LTQ Linear trap quadrupole MALDI Matrix-assisted laser desorption/ionization MS Mass spectrometry MS/MS Tandem mass spectrometry m/z Mass to charge PC Proprotein convertases pI Isoelectric point POMC Proopiomelancortin RIA Radioimmunoassay Rs Charged-reduced species TOF Time-of-flight XML EXtensible Markup Language 7 Introduction
منابع مشابه
NeuroPedia: neuropeptide database and spectral library
SUMMARY Neuropeptides are essential for cell-cell communication in neurological and endocrine physiological processes in health and disease. While many neuropeptides have been identified in previous studies, the resulting data has not been structured to facilitate further analysis by tandem mass spectrometry (MS/MS), the main technology for high-throughput neuropeptide identification. Many neur...
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MOTIVATION Identification of proteins by mass spectrometry-based proteomics requires automated interpretation of peptide tandem mass spectrometry spectra. The effectiveness of peptide identification can be greatly improved by filtering out extraneous noise peaks before the subsequent database searching steps. RESULTS Here we present a novel chemical rule-based filtering algorithm, termed CRF,...
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In todays bioinformatics, Mass spectrometry (MS) is the key technique for the identification of proteins. A prediction of spectrum peak intensities from pre computed molecular features would pave the way to better understanding of spectrometry data and improved spectrum evaluation. We propose a neural network architecture of Local Linear Map (LLM)-type for peptide prototyping and learning local...
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