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Darren J. Creek

dblp:15/11187 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2013
0000-0001-7497-7082ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
metabolomics
0.322013
mzMatch-ISO: an R tool for the annotation and relative quantification of isotope-labelled mass spectrometry data · Bioinform. 2013
IDEOM: an Excel interface for analysis of LC-MS-based metabolomics data · Bioinform. 2012
Bioinformatics and computational biology › metabolomics
LC-MS data analysis
0.112012
IDEOM: an Excel interface for analysis of LC-MS-based metabolomics data · Bioinform. 2012
Bioinformatics and computational biology › metabolomics
metabolite identification
0.112012
IDEOM: an Excel interface for analysis of LC-MS-based metabolomics data · Bioinform. 2012
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis
0.012013
mzMatch-ISO: an R tool for the annotation and relative quantification of isotope-labelled mass spectrometry data · Bioinform. 2013

Methods — techniques the papers use, named apart from their topics

statistical analysis · 0.2dynamic time warping · 0.1
YearPublicationVenuePosition
2013 mzMatch-ISO: an R tool for the annotation and relative quantification of isotope-labelled mass spectrometry data
abstract
MOTIVATION: Stable isotope-labelling experiments have recently gained increasing popularity in metabolomics studies, providing unique insights into the dynamics of metabolic fluxes, beyond the steady-state information gathered by routine mass spectrometry. However, most liquid chromatography-mass spectrometry data analysis software lacks features that enable automated annotation and relative quantification of labelled metabolite peaks. Here, we describe mzMatch-ISO, a new extension to the metabolomics analysis pipeline mzMatch.R. RESULTS: Targeted and untargeted isotope profiling using mzMatch-ISO provides a convenient visual summary of the quality and quantity of labelling for every metabolite through four types of diagnostic plots that show (i) the chromatograms of the isotope peaks of each compound in each sample group; (ii) the ratio of mono-isotopic and labelled peaks indicating the fraction of labelling; (iii) the average peak area of mono-isotopic and labelled peaks in each sample group; and (iv) the trend in the relative amount of labelling in a predetermined isotopomer. To aid further statistical analyses, the values used for generating these plots are also provided as a tab-delimited file. We demonstrate the power and versatility of mzMatch-ISO by analysing a (13)C-labelled metabolome dataset from trypanosomal parasites. AVAILABILITY: mzMatch.R and mzMatch-ISO are available free of charge from http://mzmatch.sourceforge.net and can be used on Linux and Windows platforms running the latest version of R. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Achuthanunni Chokkathukalam, Andris Jankevics, Darren J. Creek, Fiona Achcar, Michael P. Barrett, Rainer Breitling
Bioinform.3
2012 IDEOM: an Excel interface for analysis of LC-MS-based metabolomics data
abstract
SUMMARY: The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates filtering and identification of metabolite peaks, paying particular attention to common sources of noise and false identifications generated by liquid chromatography-mass spectrometry (LC-MS) platforms. Building on advanced processing tools such as mzMatch and XCMS, it allows users to run a comprehensive pipeline for data analysis and visualization from a graphical user interface within Microsoft Excel, a familiar program for most biological scientists. AVAILABILITY AND IMPLEMENTATION: IDEOM is provided free of charge at http://mzmatch.sourceforge.net/ideom.html, as a macro-enabled spreadsheet (.xlsb). Implementation requires Microsoft Excel (2007 or later). R is also required for full functionality. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Darren J. Creek, Andris Jankevics, Karl E. V. Burgess, Rainer Breitling, Michael P. Barrett
Bioinform.1