Valerie B. O'Donnell

dblp:236/1480 · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0003-4089-8460ORCID · verified

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

Applied, interdisciplinary, general and emerging computing · 2 · 1 since 2021

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
lipidomics
0.922021
LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications · Bioinform. 2021
LipidFinder on LIPID MAPS: peak filtering, MS searching and statistical analysis for lipidomics · Bioinform. 2019
Bioinformatics and computational biology
metabolomics
0.922021
LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications · Bioinform. 2021
LipidFinder on LIPID MAPS: peak filtering, MS searching and statistical analysis for lipidomics · Bioinform. 2019
Bioinformatics and computational biology › metabolomics › lipidomics
lipid identification
0.512021
LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications · Bioinform. 2021
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis
0.412019
LipidFinder on LIPID MAPS: peak filtering, MS searching and statistical analysis for lipidomics · Bioinform. 2019

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

target-decoy strategy · 0.5isotope deletion · 0.5database search · 0.5statistical analysis · 0.4LC/MS workflow · 0.4
YearPublicationVenuePosition
2021 LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications
abstract
SUMMARY: We present LipidFinder 2.0, incorporating four new modules that apply artefact filters, remove lipid and contaminant stacks, in-source fragments and salt clusters, and a new isotope deletion method which is significantly more sensitive than available open-access alternatives. We also incorporate a novel false discovery rate method, utilizing a target-decoy strategy, which allows users to assess data quality. A renewed lipid profiling method is introduced which searches three different databases from LIPID MAPS and returns bulk lipid structures only, and a lipid category scatter plot with color blind friendly pallet. An API interface with XCMS Online is made available on LipidFinder's online version. We show using real data that LipidFinder 2.0 provides a significant improvement over non-lipid metabolite filtering and lipid profiling, compared to available tools. AVAILABILITY AND IMPLEMENTATION: LipidFinder 2.0 is freely available at https://github.com/ODonnell-Lipidomics/LipidFinder and http://lipidmaps.org/resources/tools/lipidfinder. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Patricia Rodrigues, Eoin Fahy, Anne O'connor, Anna Price, Caroline Gaud, Simon Andrews, H. Paul Benton, Gary Siuzdak, Jade I Hawksworth, Maria Valdivia-Garcia, Stuart M. Allen, Valerie B. O'Donnell
Bioinform.13
2019 LipidFinder on LIPID MAPS: peak filtering, MS searching and statistical analysis for lipidomics
abstract
SUMMARY: We present LipidFinder online, hosted on the LIPID MAPS website, as a liquid chromatography/mass spectrometry (LC/MS) workflow comprising peak filtering, MS searching and statistical analysis components, highly customized for interrogating lipidomic data. The online interface of LipidFinder includes several innovations such as comprehensive parameter tuning, a MS search engine employing in-house customized, curated and computationally generated databases and multiple reporting/display options. A set of integrated statistical analysis tools which enable users to identify those features which are significantly-altered under the selected experimental conditions, thereby greatly reducing the complexity of the peaklist prior to MS searching is included. LipidFinder is presented as a highly flexible, extensible user-friendly online workflow which leverages the lipidomics knowledge base and resources of the LIPID MAPS website, long recognized as a leading global lipidomics portal. AVAILABILITY AND IMPLEMENTATION: LipidFinder on LIPID MAPS is available at: http://www.lipidmaps.org/data/LF.
Eoin Fahy, Christopher J. Brasher, Jade I Hawksworth, Patricia Rodrigues, Sven Meckelmann, Stuart M. Allen, Valerie B. O'Donnell
Bioinform.9