scholarly journals A Survey of Orbitrap All Ion Fragmentation Analysis Assessed by an R MetaboList Package to Study Small-molecule Metabolites

2018 ◽  
Author(s):  
Enrique Sentandreu ◽  
Manuel D Peris-Díaz ◽  
Shannon R Sweeney ◽  
Jennifer Chiou ◽  
Nathalie Muñoz ◽  
...  
Keyword(s):  
Data Processing ◽  
Metabolite Profiling ◽  
Accurate Determination ◽  
Leukemia Cell ◽  
R Package ◽  
High Mass ◽  
Melanoma Tumor ◽  
Ion Fragmentation ◽  
Automated Data Processing ◽  
Switching Mode

ABSTRACTLeukemia cell and melanoma tumor tissue extracts were studied for small (mostly m/z <250) polar metabolites by LC-ESI-HRMSn analysis powered by a hybrid Quadrupole-Orbitrap. MS data was simultaneously acquired in fast polarity switching mode operating in MS1 and MS/MS (All Ion Fragmentation, AIF) full-scan analyses at high mass resolution. Positive assignments were achieved by AIF analysis considering at least two characteristic transitions of metabolites. A targeted metabolite profiling was achieved by the relative quantification of 18 metabolites through spiking their respective deuterated counterparts. Manual data processing of MS1 and AIF scans were compared for accurate determination of natural metabolites and their deuterated analogs by chromatographic alignment and peak area integration. Evaluation of manual and automated (MetaboList R package) AIF data processing yielded comparable results. The versatility of AIF analysis also enabled the untargeted metabolite profiling of leukemia and melanoma samples in which 22 and 53 compounds were respectively identified outside those studied by labeling. The main limitation of the method was that low abundance metabolites with scan rates below 8 scans/peak could not be accurately quantified by AIF analysis. Combination of AIF analysis with MetaboList R package represents an opportunity to move towards automated, faster and more global metabolomics approaches supported by an entirely flexible open source automated data processing platform freely available from Comprehensive R Archive Network (CRAN, https://CRAN.R-project.org/package=MetaboList).

An integrated targeted metabolomic platform for high-throughput metabolite profiling and automated data processing

Metabolomics ◽  
2015 ◽  
Vol 11 (6) ◽  
pp. 1575-1586 ◽  
Author(s):  
Yuping Cai ◽  
Kai Weng ◽  
Yuan Guo ◽  
Jie Peng ◽  
Zheng-Jiang Zhu
Keyword(s):  
Data Processing ◽  
High Throughput ◽  
Metabolite Profiling ◽  
Automated Data Processing

Methods for reproducible shipboard SFA nutrient measurement using RMNS and automated data processing

2018 ◽  
Author(s):  
Christine Rees ◽  
Lindsay Pender ◽  
Kendall Sherrin ◽  
Cassie Schwanger ◽  
Peter Hughes ◽  
...  
Keyword(s):  
Data Processing ◽  
Automated Data Processing

Automated Data Processing and Quantification in Polymer Mass Spectrometry

2012 ◽  
pp. 237-280 ◽  
Author(s):  
Till Gruendling ◽  
William E. Wallace ◽  
Christopher Barner-Kowollik ◽  
Charles M. Guttman ◽  
Anthony J. Kearsly
Keyword(s):  
Mass Spectrometry ◽  
Data Processing ◽  
Automated Data Processing

scholarly journals From pre-emption to slowness: Assessing the contrasting temporalities of data-driven predictive policing

2020 ◽  
Vol 22 (9) ◽  
pp. 1528-1544
Author(s):  
Mark Andrejevic ◽  
Lina Dencik ◽  
Emiliano Treré
Keyword(s):  
Data Processing ◽  
Predictive Analytics ◽  
Data Driven ◽  
Temporal Shift ◽  
Predictive Policing ◽  
Social Actors ◽  
The Past ◽  
Automated Data Processing ◽  
Institutional Contexts ◽  
Conditions Of Possibility

Debates on the temporal shift associated with digitalization often stress notions of speed and acceleration. With the advent of big data and predictive analytics, the time-compressing features of digitalization are compounded within a distinct operative logic: that of pre-emption. The temporality of pre-emption attempts to project the past into a simulated future that can be acted upon in the present; a temporality of pure imminence. Yet, inherently paradoxical, pre-emption is marked by myriads of contrasts and frictions as it is caught between the supposedly all-encompassing knowledge of the data-processing ‘Machine’, and the daily reality of decision-making practices by relevant social actors. In this article, we explore the contrasting temporalities of automated data processing and predictive analytics, using policing as an illustrative example. Drawing on insights from two cases of predictive policing systems that have been implemented among UK police forces, we highlight the prevalence of counter-temporalities as predictive analytics is situated in institutional contexts and consider the conditions of possibility for agency and deliberation. Analysing these temporal tensions in relation to ‘slowness’ as a mode of resistance, the contextual examination of predictive policing advanced in the article provides a contribution to the formation of a deeper awareness of the politics of time in automated data processing; one that may serve to counter the imperative of pre-emption that, taken to the limit, seeks to foreclose the time for politics, action and life.

scholarly journals LCVP, The Leipzig catalogue of vascular plants, a new taxonomic reference list for all known vascular plants

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Martin Freiberg ◽  
Marten Winter ◽  
Alessandro Gentile ◽  
Alexander Zizka ◽  
Alexandra Nora Muellner-Riehl ◽  
...  
Keyword(s):  
Vascular Plants ◽  
Molecular Phylogenetics ◽  
Vascular Plant ◽  
Taxonomic Status ◽  
R Package ◽  
Easy Access ◽  
Reference List ◽  
Reference Information ◽  
Automated Data Processing ◽  
Similar Resource

AbstractThe lack of comprehensive and standardized taxonomic reference information is an impediment for robust plant research, e.g. in systematics, biogeography or macroecology. Here we provide an updated and much improved reference list of 1,315,562 scientific names for all described vascular plant species globally. The Leipzig Catalogue of Vascular Plants (LCVP; version 1.0.3) contains 351,180 accepted species names (plus 6,160 natural hybrids), within 13,460 genera, 564 families and 84 orders. The LCVP a) contains more information on the taxonomic status of global plant names than any other similar resource, and b) significantly improves the reliability of our knowledge by e.g. resolving the taxonomic status of ~181,000 names compared to The Plant List, the up to date most commonly used plant name resource. We used ~4,500 publications, existing relevant databases and available studies on molecular phylogenetics to construct a robust reference backbone. For easy access and integration into automated data processing pipelines, we provide an ‘R’-package (lcvplants) with the LCVP.

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