2,033 research outputs found
amsrpm: Robust Point Matching for Retention Time Aligment of LC/MS Data with R
Proteomics is the study of the abundance, function and dynamics of all proteins present in a living organism, and mass spectrometry (MS) has become its most important tool due to its unmatched sensitivity, resolution and potential for high-throughput experimentation. A frequently used variant of mass spectrometry is coupled with liquid chromatography (LC) and is denoted as "LC/MS". It produces two-dimensional raw data, where significant distortions along one of the dimensions can occur between different runs on the same instrument, and between instruments. A compensation of these distortions is required to allow for comparisons between and inference based on different experiments. This article introduces the amsrpm software package. It implements a variant of the Robust Point Matching (RPM) algorithm that is tailored for the alignment of LC and LC/MS experiments. Problem-specific enhancements include a specialized dissimilarity measure, and means to enforce smoothness and monotonicity of the estimated transformation function. The algorithm does not rely on pre-specified landmarks, it is insensitive towards outliers and capable of modeling nonlinear distortions. Its usefulness is demonstrated using both simulated and experimental data. The software is available as an open source package for the statistical programming language R.
NITPICK: peak identification for mass spectrometry data
<p>Abstract</p> <p>Background</p> <p>The reliable extraction of features from mass spectra is a fundamental step in the automated analysis of proteomic mass spectrometry (MS) experiments.</p> <p>Results</p> <p>This contribution proposes a sparse template regression approach to peak picking called NITPICK. NITPICK is a Non-greedy, Iterative Template-based peak PICKer that deconvolves complex overlapping isotope distributions in multicomponent mass spectra. NITPICK is based on <it>fractional averagine</it>, a novel extension to Senko's well-known averagine model, and on a modified version of sparse, non-negative least angle regression, for which a suitable, statistically motivated early stopping criterion has been derived. The strength of NITPICK is the deconvolution of overlapping mixture mass spectra.</p> <p>Conclusion</p> <p>Extensive comparative evaluation has been carried out and results are provided for simulated and real-world data sets. NITPICK outperforms pepex, to date the only alternate, publicly available, non-greedy feature extraction routine. NITPICK is available as software package for the R programming language and can be downloaded from <url>http://hci.iwr.uni-heidelberg.de/mip/proteomics/</url>.</p
amsrpm: Robust Point Matching for Retention Time Aligment of LC/MS Data with R
Proteomics is the study of the abundance, function and dynamics of all proteins present in a living organism, and mass spectrometry (MS) has become its most important tool due to its unmatched sensitivity, resolution and potential for high-throughput experimentation. A frequently used variant of mass spectrometry is coupled with liquid chromatography (LC) and is denoted as "LC/MS". It produces two-dimensional raw data, where significant distortions along one of the dimensions can occur between different runs on the same instrument, and between instruments. A compensation of these distortions is required to allow for comparisons between and inference based on different experiments. This article introduces the amsrpm software package. It implements a variant of the Robust Point Matching (RPM) algorithm that is tailored for the alignment of LC and LC/MS experiments. Problem-specific enhancements include a specialized dissimilarity measure, and means to enforce smoothness and monotonicity of the estimated transformation function. The algorithm does not rely on pre-specified landmarks, it is insensitive towards outliers and capable of modeling nonlinear distortions. Its usefulness is demonstrated using both simulated and experimental data. The software is available as an open source package for the statistical programming language R
EU Competitiveness in Advanced Li-ion Batteries for E-Mobility and Stationary Storage Applications – Opportunities and Actions
Projected global demand for Li-ion batteries for mobility and stationary storage applications will exceed currently available and known planned production capacities already in the near future. Conditions for establishing a globally competitive Li-ion battery value chain in the EU are identified and enabling measures that the Commission can deploy are proposed.JRC.C.1-Energy Storag
Greenhouse Gas Emissions from Fossil Fuel Fired Power Generation Systems.
Abstract not availableJRC.(IAM)-Institute For Advanced Material
A novel framework to assess the wake vortex hazards risk supported by aircraft in en-route operations
The work presented in this paper was partially funded by the SESAR
Joint Undertaking under grant agreement No 699247, as part of the European
Union’s Horizon 2020 research and innovation programme: R-WAKE project
(Wake Vortex Simulation and Analysis to Enhance En-route Separation Management
in Europe - http://www.rwake-sesar2020.eu/). TThis paper presents the simulation environment
developed within the framework of R-WAKE project, funded
by SESAR 2020 Exploratory Research. This project aims to
investigate the risks and hazards of potential wake vortex
encounters in the en-route airspace, under current and futuristic
operational scenarios, in order to support new separation
standards aimed at increasing airspace capacity. The R-WAKE
simulation environment integrates different components developed
by different partners of the R-WAKE consortium, including
simulators for weather, traffic, wake vortex phenomena, wake
vortex interactions and different tools and methodologies for
safety and risk assessment. A preliminary example is presented
in this paper, in which 200 historical trajectories were simulated
to show that the novel framework works properly. A WVE
encounter has been detected in such first scenario, however with
no significant safety effect on the follower aircraft. A second
controlled scenario has been then run to force the detection of a
severe wake encounter under realistic en-route conditions. Such
scenario has given evidences that confirm the safety relevance of
the underlying research concept.Peer ReviewedPostprint (published version
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