Label-free quantification of high mass resolution LC-MS data has emerged as a promising technology for proteome analysis. Computational methods are required for the accurate extraction of peptide signals from LC-MS data and the tracking of these features across the measurements of different samples. We present here an open source software tool, SuperHirn, that comprises a set of modules to process LC-MS data acquired on a high resolution mass spectrometer. The program includes newly developed functionalities to analyze LC-MS data such as feature extraction and quantification, LC-MS similarity analysis, LC-MS alignment of multiple datasets, and intensity normalization. These program routines extract profiles of measured features and comprise tools for clustering and classification analysis of the profiles. SuperHirn was applied in an MS1-based profiling approach to a benchmark LC-MS dataset of complex protein mixtures with defined concentration changes. We show that the program automatically detects profiling trends in an unsupervised manner and is able to associate proteins to their correct theoretical dilution profile.
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Publication date: Available online 4 January 2018 Source: European Journal of Radiology Author(s): Peiyao Zhang, Jing Wang, Qin Xu, Zhen...
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Publication date: March 2017 Source: Free Radical Biology and Medicine, Volume 104 from #AlexandrosSfakianakis via Alexandros G.Sfak...
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Dtsch med Wochenschr DOI: 10.1055/s-0043-100054 Hintergrund und Fragestellung Ein etablierter Weg, die optimale Behandlung von Tumorpatien...
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Background Hyperthyroidism is associated with increased thrombotic risk. As contact system activation through formation of neutrophil extrac...
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Deepak Thapa, Vanita Ahuja, Deepanshu Dhiman Indian Journal of Anaesthesia 2017 61(12):1012-1014 from #AlexandrosSfakianakis via Alexa...
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BACKGROUND AND PURPOSE: Dengue is a common arboviral disease, which uncommonly involves the brain. There has been a recent surge in dengu...
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Abstract Limited memory size is considered as a major bottleneck in data centers for intelligent urban computing. It is shown that there e...
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Vol.36 No.6 from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/1k8FKtW via IFTTT
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Linked Article: Maintz et al. Br J Dermatol 2017; 176:481–487 . from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader h...
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